If you're seeing this message, it means we're having trouble loading external resources on our website.

If you're behind a web filter, please make sure that the domains *.kastatic.org and *.kasandbox.org are unblocked.

To log in and use all the features of Khan Academy, please enable JavaScript in your browser.

AP®︎/College Statistics

Course: ap®︎/college statistics   >   unit 10.

  • Idea behind hypothesis testing

Examples of null and alternative hypotheses

  • Writing null and alternative hypotheses
  • P-values and significance tests
  • Comparing P-values to different significance levels
  • Estimating a P-value from a simulation
  • Estimating P-values from simulations
  • Using P-values to make conclusions

example sentence of alternative hypothesis

Want to join the conversation?

  • Upvote Button navigates to signup page
  • Downvote Button navigates to signup page
  • Flag Button navigates to signup page

Good Answer

Video transcript

Examples

Alternative Hypothesis

Ai generator.

example sentence of alternative hypothesis

Diving deep into the realm of scientific research, the alternative hypothesis plays a pivotal role in steering investigations. It stands contrary to the null hypothesis , providing a different perspective or direction. This essential component often sets the foundation for groundbreaking discoveries. If you’re keen on understanding this concept further, our collection of alternative hypothesis statement examples, combined with a thorough writing guide and insightful tips, will serve as your comprehensive roadmap.

What is an Alternative hypothesis?

An alternative hypothesis is a statement used in statistical testing that indicates the presence of an effect, relationship, or difference. It stands in direct contrast to the null hypothesis, which posits that there is no effect or relationship. The alternative causual hypothesis provides a specific direction to the research and can be directional (e.g., one value is greater than another) or non-directional (e.g., two values are not equal).

What is an example of an Alternative hypothesis statement?

If a researcher is studying the effect of a new teaching method on student performance, the null hypothesis might be: “The new teaching method has no effect on student performance.” An example of an alternative hypothesis could be:

Directional: “Students exposed to the new teaching method will perform better than those who were not.” Non-directional: “Student performance will be different for those exposed to the new teaching method compared to those who were not.”

100 Alternative Hypothesis Statement Examples

Alternative Hypothesis Statement Examples

Size: 188 KB

The alternative hypothesis symbolizes a statement of what a statistical hypothesis test is set to establish. Often contrasted with a null hypothesis, it indicates the expected direction of the tested relation. Dive into these varied thesis statement examples showcasing the core essence of alternative hypotheses.

  • Smoking and Cancer : Smoking is positively related to lung cancer incidence.
  • Diet and Weight Loss : The Atkins diet results in more weight loss than a conventional diet.
  • Medication Efficiency : Drug A is more effective than Drug B in treating migraines.
  • Exercise Duration : Engaging in physical activity for more than 30 minutes daily reduces depression symptoms.
  • Class Size and Learning : Smaller class sizes lead to higher student test scores.
  • Sugar Intake : Consuming more than 50 grams of sugar daily increases the risk of diabetes.
  • Vitamin C and Cold : Vitamin C intake reduces the duration of the common cold.
  • Sleep Duration : Sleeping less than 6 hours results in decreased cognitive function.
  • Training Methods : Method X training increases employee productivity more than Method Y.
  • Pollution Levels : Higher levels of industrial activity correlate with increased air pollution.
  • Stress and Disease : Chronic stress has a positive relationship with heart diseases.
  • Alcohol and Reaction Time : Alcohol consumption slows down reaction time.
  • Meditation and Blood Pressure : Regular meditation lowers blood pressure.
  • Organic Food : Consuming organic food leads to better gut health.
  • Advertising : Increased advertising results in higher sales figures.
  • Salary and Job Satisfaction : A higher salary correlates with job satisfaction.
  • Age and Memory : As age increases, short-term memory retention decreases.
  • Temperature and Aggression : Higher temperatures are associated with increased aggressive behavior.
  • Social Media : Spending more than 2 hours on social media daily increases feelings of loneliness.
  • Music and Concentration : Listening to classical music improves concentration during studies. …
  • Recycling Habits : Communities with mandatory recycling policies have higher recycling rates.
  • Urban Areas : Living in urban areas increases the likelihood of asthma.
  • Pets and Loneliness : Owning a pet decreases feelings of loneliness.
  • Reading Habits : Reading more than 3 books a month correlates with increased empathy.
  • Green Spaces : Having access to green spaces reduces stress levels.
  • Vaccination : Vaccination reduces the incidence of specific diseases.
  • Chocolate and Mood : Consuming chocolate elevates mood.
  • Remote Work : Working remotely improves overall work satisfaction.
  • Financial Literacy : Financial literacy education reduces personal debt.
  • Mindfulness and Anxiety : Practicing mindfulness decreases symptoms of anxiety. …
  • Dietary Fiber : Higher dietary fiber intake is associated with lower risks of bowel cancer.
  • Travel and Creativity : People who travel frequently are more creative.
  • Education Level and Income : Individuals with higher education levels earn more income.
  • Technology Adoption : People who receive technology training adapt to new devices faster.
  • Parental Involvement and Academic Performance : Increased parental involvement enhances students’ academic performance.
  • Exercise Frequency and Heart Health : Exercising at least five times a week improves heart health.
  • Gender and Leadership Roles : Men are more likely to hold leadership positions in corporate settings.
  • Social Support and Mental Health : Strong social support networks reduce the risk of depression.
  • Quality of Sleep and Productivity : Better sleep quality leads to higher productivity levels.
  • High-Fat Diet and Cholesterol Levels : A high-fat diet increases cholesterol levels.
  • Caffeine Intake and Alertness : Higher caffeine intake enhances alertness and cognitive function.
  • Online Shopping Habits : People who frequently shop online spend more money than in-store shoppers. …
  • Education and Political Views : Higher education levels are associated with more liberal political views.
  • Gender and Risk-Taking Behavior : Men are more likely to engage in risky behaviors.
  • Temperature and Ice Cream Sales : Higher temperatures increase ice cream sales.
  • Artificial Sweeteners and Weight Loss : Consuming products with artificial sweeteners aids in weight loss.
  • Exercise and Stress Reduction : Regular exercise reduces stress levels.
  • Music Genres and Mood : Listening to upbeat music improves mood.
  • Online Learning and Engagement : Online learners are more engaged in virtual classroom discussions.
  • Personality Traits and Job Performance : Extroverted individuals perform better in sales roles.
  • Environmental Awareness and Recycling : Higher environmental awareness leads to more recycling practices.
  • Social Media Usage and Self-Esteem : Excessive social media usage correlates with lower self-esteem. …
  • Sleep Deprivation and Reaction Time : Sleep-deprived individuals have slower reaction times.
  • Breakfast Consumption and Metabolism : Eating breakfast kickstarts metabolism for the day.
  • Leadership Style and Employee Satisfaction : Transformational leadership style increases employee job satisfaction.
  • Bilingualism and Cognitive Abilities : Bilingual individuals possess enhanced cognitive abilities.
  • Video Game Playing and Aggression : Playing violent video games increases aggressive behavior.
  • Hydration and Cognitive Function : Staying hydrated improves cognitive function.
  • Parental Support and Academic Achievement : Supportive parenting leads to higher academic achievement.
  • Workplace Flexibility and Work-Life Balance : Jobs with flexible schedules enhance work-life balance.
  • Digital Learning and Knowledge Retention : Digital learning methods improve long-term knowledge retention.
  • Art Exposure and Creativity : Exposure to various forms of art fosters creative thinking.
  • Solar Energy Adoption and Utility Bills : Homes with solar energy systems experience lower utility bills.
  • Parental Involvement and Student Behavior : Increased parental involvement reduces student behavioral issues.
  • Team Diversity and Creativity : Diverse teams generate more creative solutions.
  • Social Media Marketing and Brand Awareness : Social media marketing boosts brand awareness more than traditional methods.
  • Morning Routine and Productivity : Following a structured morning routine enhances overall productivity.
  • Music Training and Cognitive Development : Music training improves cognitive abilities in children.
  • Employee Training and Job Satisfaction : Comprehensive employee training programs lead to higher job satisfaction.
  • Eating Before Bed and Sleep Quality : Consuming heavy meals before bed negatively affects sleep quality.
  • Financial Incentives and Employee Performance : Offering financial incentives increases employee performance.
  • Parental Attachment and Emotional Well-being : Strong parental attachment fosters better emotional well-being in children.
  • Social Interaction and Mental Well-being : Frequent social interaction correlates with improved mental health.
  • Education and Crime Rates : Higher education levels result in lower crime rates within communities.
  • Diet and Acne : A diet high in dairy products exacerbates acne.
  • Leadership Style and Employee Motivation : Autocratic leadership style hampers employee motivation.
  • Urban Green Spaces and Stress Reduction : Access to urban green spaces lowers stress levels.
  • Sleep Duration and Athletic Performance : Adequate sleep duration enhances athletic performance.
  • Financial Literacy and Investment Success : Individuals with high financial literacy make more successful investments.
  • Team Collaboration and Project Success : Effective team collaboration leads to more successful project outcomes.
  • Media Exposure and Body Image : Increased media exposure contributes to negative body image perceptions.
  • Gender Representation and Film Success : Movies with more balanced gender representation achieve higher box office success. …
  • Meditation and Anxiety Reduction : Regular meditation practice reduces symptoms of anxiety.
  • Cognitive Training and Memory Enhancement : Cognitive training programs improve memory retention.
  • Positive Affirmations and Self-Confidence : Repeating positive affirmations enhances self-confidence.
  • Physical Fitness and Longevity : Being physically fit is linked to increased lifespan.
  • Parental Guidance and Online Safety : Strong parental guidance promotes responsible online behavior in children.
  • Artificial Intelligence and Job Displacement : Increased AI integration leads to more job displacement.
  • Public Transportation Usage and Air Quality : Increased public transportation usage improves air quality in cities.
  • Social Support and Addiction Recovery : Strong social support networks aid in addiction recovery.
  • Gender Diversity and Company Performance : Companies with diverse gender representation outperform others.
  • Mindfulness Meditation and Pain Management : Mindfulness meditation reduces perception of pain.
  • Music Therapy and Autism : Music therapy improves social interaction skills in children with autism.
  • Social Media Usage and Academic Performance : Excessive social media usage negatively impacts academic performance.
  • Employee Engagement and Organizational Success : Higher employee engagement leads to greater organizational success.
  • Healthy Eating and Longevity : A diet rich in fruits and vegetables contributes to a longer lifespan.
  • Gender Stereotypes and Career Choice : Gender stereotypes influence career choices among young adults.
  • Environmental Conservation Efforts and Biodiversity : Increased conservation efforts positively affect biodiversity.
  • Volunteerism and Personal Well-being : Engaging in volunteer activities enhances personal well-being.
  • Artificial Intelligence and Customer Service : AI-driven customer service improves user satisfaction.

Alternative Hypothesis Statement Examples in Research

In alternative research hypothesis propel investigations beyond the null. Examples span diverse fields, revealing the direction researchers expect their findings to take.

  • Effect of Music on Concentration : Listening to classical music enhances concentration during study.
  • Green Tea and Weight Loss : Green tea consumption leads to more significant weight loss than water intake.
  • Parental Involvement and Academic Achievement : Active parental involvement boosts student academic achievement.
  • Social Media Usage and Self-Esteem : Frequent social media use correlates with lower self-esteem.

Alternative Hypothesis Statement Examples in Business Research

Business research thrives on alternative hypotheses. Dive into these business-oriented examples that challenge null assumptions.

  • Marketing Campaign Impact : Marketing campaign A generates higher conversion rates than campaign B.
  • Employee Training and Productivity : Comprehensive employee training enhances workplace productivity.
  • Work-Life Balance and Employee Satisfaction : Improved work-life balance increases employee job satisfaction.
  • Customer Service Channel Effectiveness : Online chat support results in higher customer satisfaction compared to phone support.
  • Branding Influence on Purchase Intent : Strong brand presence leads to increased purchase intent.

Directional Alternative Hypothesis Statement Examples

Directional hypothesis add clarity to research expectations. Explore these examples that predict specific outcomes.

  • Exercise Frequency and Heart Health : Engaging in physical activity five times a week improves heart health.

Alternative Hypothesis Statement Examples in Psychology

Psychological studies benefit from well-crafted alternative hypotheses. These psychology hypothesis examples delve into the realm of human behavior and cognition.

  • Mindfulness Meditation and Anxiety Reduction : Regular mindfulness practice reduces symptoms of anxiety.

Alternative Null Hypothesis Statement Examples

Explore alternative null hypothesis —statements asserting the absence of specific effects or differences.

  • Coffee Consumption and Weight Gain : Increased coffee consumption does not lead to weight gain.
  • Smartphone Usage and Sleep Quality : Using smartphones before bed does not impact sleep quality.
  • Music Genre and Study Performance : Studying with rock music does not affect academic performance.
  • Green Spaces and Stress Reduction : Access to green spaces does not decrease stress levels.
  • Team Diversity and Project Success : Team diversity does not influence project success rates.

Alternative Hypothesis Statement Examples in Medical Research

Medical research relies on robust alternative hypotheses to drive scientific inquiry. These examples explore hypotheses in the realm of healthcare.

  • Exercise and Diabetes Prevention : Regular exercise decreases the risk of developing type 2 diabetes.
  • Medication A and Blood Pressure Reduction : Medication A leads to greater reduction in blood pressure compared to medication B.
  • Nutritional Intake and Heart Disease : Higher intake of fruits and vegetables lowers the risk of heart disease.
  • Stress Reduction Techniques and Anxiety Levels : Practicing stress reduction techniques decreases anxiety levels.
  • Alternative Medicine and Pain Management : Alternative medicine therapies alleviate chronic pain more effectively than traditional treatments.

Alternative Hypothesis Statement Examples in Education Research

Education research thrives on alternative hypotheses to investigate innovative approaches. Explore examples that challenge conventional notions.

  • Technology Integration and Student Engagement : Integrating technology enhances student engagement in the classroom.
  • Project-Based Learning and Knowledge Retention : Project-based learning improves long-term knowledge retention.
  • Teacher Professional Development and Student Performance : Effective teacher professional development positively impacts student academic performance.
  • Inclusive Classroom Environment and Learning Outcomes : Inclusive classrooms lead to better learning outcomes for diverse students.
  • Feedback Frequency and Writing Improvement : Frequent feedback results in greater improvement in student writing skills.

These examples showcase the pivotal role of alternative hypotheses across various disciplines, serving as the driving force behind scientific exploration and advancement.

What is the Alternative Hypothesis Formula?

The alternative hypothesis, denoted as “Ha” or “H1,” represents the assertion researchers aim to support through evidence. It stands in contrast to the null hypothesis (Ho), which suggests no effect or relationship. The formula for the alternative hypothesis varies based on the nature of the study:

  • Directional Hypothesis : For studies with an expected direction, the formula takes the form of a prediction. For instance, “The new drug increases patient recovery rates.”
  • Non-Directional Hypothesis : For exploratory studies, the formula reflects the possibility of any difference or effect. For example, “There is a difference in recovery rates between the two drugs.”

How do you start an Alternative Hypothesis?

Starting an alternative simple hypothesis involves framing a clear research statement that highlights the anticipated effect, relationship, or difference. To begin:

  • Identify the Research Question: Determine the specific aspect you intend to explore or compare.
  • Formulate a Hypothesis: Craft a statement that directly addresses the expected outcome.
  • Include Variables: Introduce the relevant variables and their predicted connection.
  • Be Clear and Specific: Ensure the alternative hypothesis is concise and unambiguous.

Is the Alternative Hypothesis a Claim or Statement?

The alternative hypothesis is both a claim and a statement. It claims that there is a measurable effect, relationship, or difference in the variables being studied. It is also a statement that researchers work to validate through evidence.

How do you write an Alternative Hypothesis Statement? – Step by Step Guide

Creating a robust alternative hypothesis statement involves structured steps:

  • Identify Variables : Clearly define the independent and dependent variables in your study.
  • State Expected Effect : Express the anticipated impact, relationship, or difference between variables.
  • Be Precise : Use specific language to convey the exact nature of the expected outcome.
  • Include Direction (if applicable) : If your hypothesis is directional, specify the expected direction.
  • Avoid Ambiguity : Make sure your statement is clear and leaves no room for confusion.

Tips for Writing an Alternative Hypothesis Statement

  • Be Specific : Clearly define the variables and the predicted relationship.
  • Use Measurable Terms : Incorporate quantifiable terms to indicate the magnitude of the effect.
  • Testability : Ensure the hypothesis can be tested empirically.
  • Conciseness : Keep the statement concise and to the point.
  • Alignment with Research Question : Ensure the hypothesis directly answers your research question.
  • Avoid Value Judgments : Avoid value judgments or personal biases in the hypothesis.
  • Review Literature : Consult existing literature to align your hypothesis with prior research.

Crafting a strong alternative hypothesis statement is essential for guiding your research and forming the basis for causual hypothesis testing. It directs the focus of your investigation and lays the foundation for drawing meaningful conclusions.

Twitter

Text prompt

  • Instructive
  • Professional

10 Examples of Public speaking

20 Examples of Gas lighting

Module 9: Hypothesis Testing With One Sample

Null and alternative hypotheses, learning outcomes.

  • Describe hypothesis testing in general and in practice

The actual test begins by considering two  hypotheses . They are called the null hypothesis and the alternative hypothesis . These hypotheses contain opposing viewpoints.

H 0 : The null hypothesis: It is a statement about the population that either is believed to be true or is used to put forth an argument unless it can be shown to be incorrect beyond a reasonable doubt.

H a : The alternative hypothesis : It is a claim about the population that is contradictory to H 0 and what we conclude when we reject H 0 .

Since the null and alternative hypotheses are contradictory, you must examine evidence to decide if you have enough evidence to reject the null hypothesis or not. The evidence is in the form of sample data.

After you have determined which hypothesis the sample supports, you make adecision. There are two options for a  decision . They are “reject H 0 ” if the sample information favors the alternative hypothesis or “do not reject H 0 ” or “decline to reject H 0 ” if the sample information is insufficient to reject the null hypothesis.

Mathematical Symbols Used in  H 0 and H a :

H 0 always has a symbol with an equal in it. H a never has a symbol with an equal in it. The choice of symbol depends on the wording of the hypothesis test. However, be aware that many researchers (including one of the co-authors in research work) use = in the null hypothesis, even with > or < as the symbol in the alternative hypothesis. This practice is acceptable because we only make the decision to reject or not reject the null hypothesis.

H 0 : No more than 30% of the registered voters in Santa Clara County voted in the primary election. p ≤ 30

H a : More than 30% of the registered voters in Santa Clara County voted in the primary election. p > 30

A medical trial is conducted to test whether or not a new medicine reduces cholesterol by 25%. State the null and alternative hypotheses.

H 0 : The drug reduces cholesterol by 25%. p = 0.25

H a : The drug does not reduce cholesterol by 25%. p ≠ 0.25

We want to test whether the mean GPA of students in American colleges is different from 2.0 (out of 4.0). The null and alternative hypotheses are:

H 0 : μ = 2.0

H a : μ ≠ 2.0

We want to test whether the mean height of eighth graders is 66 inches. State the null and alternative hypotheses. Fill in the correct symbol (=, ≠, ≥, <, ≤, >) for the null and alternative hypotheses. H 0 : μ __ 66 H a : μ __ 66

  • H 0 : μ = 66
  • H a : μ ≠ 66

We want to test if college students take less than five years to graduate from college, on the average. The null and alternative hypotheses are:

H 0 : μ ≥ 5

H a : μ < 5

We want to test if it takes fewer than 45 minutes to teach a lesson plan. State the null and alternative hypotheses. Fill in the correct symbol ( =, ≠, ≥, <, ≤, >) for the null and alternative hypotheses. H 0 : μ __ 45 H a : μ __ 45

  • H 0 : μ ≥ 45
  • H a : μ < 45

In an issue of U.S. News and World Report , an article on school standards stated that about half of all students in France, Germany, and Israel take advanced placement exams and a third pass. The same article stated that 6.6% of U.S. students take advanced placement exams and 4.4% pass. Test if the percentage of U.S. students who take advanced placement exams is more than 6.6%. State the null and alternative hypotheses.

H 0 : p ≤ 0.066

H a : p > 0.066

On a state driver’s test, about 40% pass the test on the first try. We want to test if more than 40% pass on the first try. Fill in the correct symbol (=, ≠, ≥, <, ≤, >) for the null and alternative hypotheses. H 0 : p __ 0.40 H a : p __ 0.40

  • H 0 : p = 0.40
  • H a : p > 0.40

Concept Review

In a  hypothesis test , sample data is evaluated in order to arrive at a decision about some type of claim. If certain conditions about the sample are satisfied, then the claim can be evaluated for a population. In a hypothesis test, we: Evaluate the null hypothesis , typically denoted with H 0 . The null is not rejected unless the hypothesis test shows otherwise. The null statement must always contain some form of equality (=, ≤ or ≥) Always write the alternative hypothesis , typically denoted with H a or H 1 , using less than, greater than, or not equals symbols, i.e., (≠, >, or <). If we reject the null hypothesis, then we can assume there is enough evidence to support the alternative hypothesis. Never state that a claim is proven true or false. Keep in mind the underlying fact that hypothesis testing is based on probability laws; therefore, we can talk only in terms of non-absolute certainties.

Formula Review

H 0 and H a are contradictory.

  • OpenStax, Statistics, Null and Alternative Hypotheses. Provided by : OpenStax. Located at : http://cnx.org/contents/[email protected]:58/Introductory_Statistics . License : CC BY: Attribution
  • Introductory Statistics . Authored by : Barbara Illowski, Susan Dean. Provided by : Open Stax. Located at : http://cnx.org/contents/[email protected] . License : CC BY: Attribution . License Terms : Download for free at http://cnx.org/contents/[email protected]
  • Simple hypothesis testing | Probability and Statistics | Khan Academy. Authored by : Khan Academy. Located at : https://youtu.be/5D1gV37bKXY . License : All Rights Reserved . License Terms : Standard YouTube License

9.1 Null and Alternative Hypotheses

The actual test begins by considering two hypotheses . They are called the null hypothesis and the alternative hypothesis . These hypotheses contain opposing viewpoints.

H 0 , the — null hypothesis: a statement of no difference between sample means or proportions or no difference between a sample mean or proportion and a population mean or proportion. In other words, the difference equals 0.

H a —, the alternative hypothesis: a claim about the population that is contradictory to H 0 and what we conclude when we reject H 0 .

Since the null and alternative hypotheses are contradictory, you must examine evidence to decide if you have enough evidence to reject the null hypothesis or not. The evidence is in the form of sample data.

After you have determined which hypothesis the sample supports, you make a decision. There are two options for a decision. They are reject H 0 if the sample information favors the alternative hypothesis or do not reject H 0 or decline to reject H 0 if the sample information is insufficient to reject the null hypothesis.

Mathematical Symbols Used in H 0 and H a :

H 0 always has a symbol with an equal in it. H a never has a symbol with an equal in it. The choice of symbol depends on the wording of the hypothesis test. However, be aware that many researchers use = in the null hypothesis, even with > or < as the symbol in the alternative hypothesis. This practice is acceptable because we only make the decision to reject or not reject the null hypothesis.

Example 9.1

H 0 : No more than 30 percent of the registered voters in Santa Clara County voted in the primary election. p ≤ 30 H a : More than 30 percent of the registered voters in Santa Clara County voted in the primary election. p > 30

A medical trial is conducted to test whether or not a new medicine reduces cholesterol by 25 percent. State the null and alternative hypotheses.

Example 9.2

We want to test whether the mean GPA of students in American colleges is different from 2.0 (out of 4.0). The null and alternative hypotheses are the following: H 0 : μ = 2.0 H a : μ ≠ 2.0

We want to test whether the mean height of eighth graders is 66 inches. State the null and alternative hypotheses. Fill in the correct symbol (=, ≠, ≥, <, ≤, >) for the null and alternative hypotheses.

  • H 0 : μ __ 66
  • H a : μ __ 66

Example 9.3

We want to test if college students take fewer than five years to graduate from college, on the average. The null and alternative hypotheses are the following: H 0 : μ ≥ 5 H a : μ < 5

We want to test if it takes fewer than 45 minutes to teach a lesson plan. State the null and alternative hypotheses. Fill in the correct symbol ( =, ≠, ≥, <, ≤, >) for the null and alternative hypotheses.

  • H 0 : μ __ 45
  • H a : μ __ 45

Example 9.4

An article on school standards stated that about half of all students in France, Germany, and Israel take advanced placement exams and a third of the students pass. The same article stated that 6.6 percent of U.S. students take advanced placement exams and 4.4 percent pass. Test if the percentage of U.S. students who take advanced placement exams is more than 6.6 percent. State the null and alternative hypotheses. H 0 : p ≤ 0.066 H a : p > 0.066

On a state driver’s test, about 40 percent pass the test on the first try. We want to test if more than 40 percent pass on the first try. Fill in the correct symbol (=, ≠, ≥, <, ≤, >) for the null and alternative hypotheses.

  • H 0 : p __ 0.40
  • H a : p __ 0.40

Collaborative Exercise

Bring to class a newspaper, some news magazines, and some internet articles. In groups, find articles from which your group can write null and alternative hypotheses. Discuss your hypotheses with the rest of the class.

As an Amazon Associate we earn from qualifying purchases.

This book may not be used in the training of large language models or otherwise be ingested into large language models or generative AI offerings without OpenStax's permission.

Want to cite, share, or modify this book? This book uses the Creative Commons Attribution License and you must attribute Texas Education Agency (TEA). The original material is available at: https://www.texasgateway.org/book/tea-statistics . Changes were made to the original material, including updates to art, structure, and other content updates.

Access for free at https://openstax.org/books/statistics/pages/1-introduction
  • Authors: Barbara Illowsky, Susan Dean
  • Publisher/website: OpenStax
  • Book title: Statistics
  • Publication date: Mar 27, 2020
  • Location: Houston, Texas
  • Book URL: https://openstax.org/books/statistics/pages/1-introduction
  • Section URL: https://openstax.org/books/statistics/pages/9-1-null-and-alternative-hypotheses

© Jan 23, 2024 Texas Education Agency (TEA). The OpenStax name, OpenStax logo, OpenStax book covers, OpenStax CNX name, and OpenStax CNX logo are not subject to the Creative Commons license and may not be reproduced without the prior and express written consent of Rice University.

  • Math Article

Alternative Hypothesis

Class Registration Banner

Alternative hypothesis defines there is a statistically important relationship between two variables. Whereas null hypothesis states there is no statistical relationship between the two variables. In statistics, we usually come across various kinds of hypotheses. A statistical hypothesis is supposed to be a working statement which is assumed to be logical with given data. It should be noticed that a hypothesis is neither considered true nor false.

The alternative hypothesis is a statement used in statistical inference experiment. It is contradictory to the null hypothesis and denoted by H a or H 1 . We can also say that it is simply an alternative to the null. In hypothesis testing, an alternative theory is a statement which a researcher is testing. This statement is true from the researcher’s point of view and ultimately proves to reject the null to replace it with an alternative assumption. In this hypothesis, the difference between two or more variables is predicted by the researchers, such that the pattern of data observed in the test is not due to chance.

To check the water quality of a river for one year, the researchers are doing the observation. As per the null hypothesis, there is no change in water quality in the first half of the year as compared to the second half. But in the alternative hypothesis, the quality of water is poor in the second half when observed.

Difference Between Null and Alternative Hypothesis

Basically, there are three types of the alternative hypothesis, they are;

Left-Tailed : Here, it is expected that the sample proportion (π) is less than a specified value which is denoted by π 0 , such that;

H 1 : π < π 0

Right-Tailed: It represents that the sample proportion (π) is greater than some value, denoted by π 0 .

H 1 : π > π 0

Two-Tailed: According to this hypothesis, the sample proportion (denoted by π) is not equal to a specific value which is represented by π 0 .

H 1 : π ≠ π 0

Note: The null hypothesis for all the three alternative hypotheses, would be H 1 : π = π 0 .

example sentence of alternative hypothesis

Register with BYJU'S & Download Free PDFs

Register with byju's & watch live videos.

Library homepage

  • school Campus Bookshelves
  • menu_book Bookshelves
  • perm_media Learning Objects
  • login Login
  • how_to_reg Request Instructor Account
  • hub Instructor Commons

Margin Size

  • Download Page (PDF)
  • Download Full Book (PDF)
  • Periodic Table
  • Physics Constants
  • Scientific Calculator
  • Reference & Cite
  • Tools expand_more
  • Readability

selected template will load here

This action is not available.

Statistics LibreTexts

8.1.1: Null and Alternative Hypotheses

  • Last updated
  • Save as PDF
  • Page ID 10971

\( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

\( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

\( \newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\)

( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\)

\( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

\( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\)

\( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

\( \newcommand{\Span}{\mathrm{span}}\)

\( \newcommand{\id}{\mathrm{id}}\)

\( \newcommand{\kernel}{\mathrm{null}\,}\)

\( \newcommand{\range}{\mathrm{range}\,}\)

\( \newcommand{\RealPart}{\mathrm{Re}}\)

\( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

\( \newcommand{\Argument}{\mathrm{Arg}}\)

\( \newcommand{\norm}[1]{\| #1 \|}\)

\( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\AA}{\unicode[.8,0]{x212B}}\)

\( \newcommand{\vectorA}[1]{\vec{#1}}      % arrow\)

\( \newcommand{\vectorAt}[1]{\vec{\text{#1}}}      % arrow\)

\( \newcommand{\vectorB}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

\( \newcommand{\vectorC}[1]{\textbf{#1}} \)

\( \newcommand{\vectorD}[1]{\overrightarrow{#1}} \)

\( \newcommand{\vectorDt}[1]{\overrightarrow{\text{#1}}} \)

\( \newcommand{\vectE}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash{\mathbf {#1}}}} \)

The actual test begins by considering two hypotheses . They are called the null hypothesis and the alternative hypothesis . These hypotheses contain opposing viewpoints.

\(H_0\): The null hypothesis: It is a statement of no difference between the variables—they are not related. This can often be considered the status quo and as a result if you cannot accept the null it requires some action.

\(H_a\): The alternative hypothesis: It is a claim about the population that is contradictory to \(H_0\) and what we conclude when we reject \(H_0\). This is usually what the researcher is trying to prove.

Since the null and alternative hypotheses are contradictory, you must examine evidence to decide if you have enough evidence to reject the null hypothesis or not. The evidence is in the form of sample data.

After you have determined which hypothesis the sample supports, you make a decision. There are two options for a decision. They are "reject \(H_0\)" if the sample information favors the alternative hypothesis or "do not reject \(H_0\)" or "decline to reject \(H_0\)" if the sample information is insufficient to reject the null hypothesis.

\(H_{0}\) always has a symbol with an equal in it. \(H_{a}\) never has a symbol with an equal in it. The choice of symbol depends on the wording of the hypothesis test. However, be aware that many researchers (including one of the co-authors in research work) use = in the null hypothesis, even with > or < as the symbol in the alternative hypothesis. This practice is acceptable because we only make the decision to reject or not reject the null hypothesis.

Example \(\PageIndex{1}\)

  • \(H_{0}\): No more than 30% of the registered voters in Santa Clara County voted in the primary election. \(p \leq 30\)
  • \(H_{a}\): More than 30% of the registered voters in Santa Clara County voted in the primary election. \(p > 30\)

Exercise \(\PageIndex{1}\)

A medical trial is conducted to test whether or not a new medicine reduces cholesterol by 25%. State the null and alternative hypotheses.

  • \(H_{0}\): The drug reduces cholesterol by 25%. \(p = 0.25\)
  • \(H_{a}\): The drug does not reduce cholesterol by 25%. \(p \neq 0.25\)

Example \(\PageIndex{2}\)

We want to test whether the mean GPA of students in American colleges is different from 2.0 (out of 4.0). The null and alternative hypotheses are:

  • \(H_{0}: \mu = 2.0\)
  • \(H_{a}: \mu \neq 2.0\)

Exercise \(\PageIndex{2}\)

We want to test whether the mean height of eighth graders is 66 inches. State the null and alternative hypotheses. Fill in the correct symbol \((=, \neq, \geq, <, \leq, >)\) for the null and alternative hypotheses.

  • \(H_{0}: \mu \_ 66\)
  • \(H_{a}: \mu \_ 66\)
  • \(H_{0}: \mu = 66\)
  • \(H_{a}: \mu \neq 66\)

Example \(\PageIndex{3}\)

We want to test if college students take less than five years to graduate from college, on the average. The null and alternative hypotheses are:

  • \(H_{0}: \mu \geq 5\)
  • \(H_{a}: \mu < 5\)

Exercise \(\PageIndex{3}\)

We want to test if it takes fewer than 45 minutes to teach a lesson plan. State the null and alternative hypotheses. Fill in the correct symbol ( =, ≠, ≥, <, ≤, >) for the null and alternative hypotheses.

  • \(H_{0}: \mu \_ 45\)
  • \(H_{a}: \mu \_ 45\)
  • \(H_{0}: \mu \geq 45\)
  • \(H_{a}: \mu < 45\)

Example \(\PageIndex{4}\)

In an issue of U. S. News and World Report , an article on school standards stated that about half of all students in France, Germany, and Israel take advanced placement exams and a third pass. The same article stated that 6.6% of U.S. students take advanced placement exams and 4.4% pass. Test if the percentage of U.S. students who take advanced placement exams is more than 6.6%. State the null and alternative hypotheses.

  • \(H_{0}: p \leq 0.066\)
  • \(H_{a}: p > 0.066\)

Exercise \(\PageIndex{4}\)

On a state driver’s test, about 40% pass the test on the first try. We want to test if more than 40% pass on the first try. Fill in the correct symbol (\(=, \neq, \geq, <, \leq, >\)) for the null and alternative hypotheses.

  • \(H_{0}: p \_ 0.40\)
  • \(H_{a}: p \_ 0.40\)
  • \(H_{0}: p = 0.40\)
  • \(H_{a}: p > 0.40\)

COLLABORATIVE EXERCISE

Bring to class a newspaper, some news magazines, and some Internet articles . In groups, find articles from which your group can write null and alternative hypotheses. Discuss your hypotheses with the rest of the class.

In a hypothesis test , sample data is evaluated in order to arrive at a decision about some type of claim. If certain conditions about the sample are satisfied, then the claim can be evaluated for a population. In a hypothesis test, we:

  • Evaluate the null hypothesis , typically denoted with \(H_{0}\). The null is not rejected unless the hypothesis test shows otherwise. The null statement must always contain some form of equality \((=, \leq \text{or} \geq)\)
  • Always write the alternative hypothesis , typically denoted with \(H_{a}\) or \(H_{1}\), using less than, greater than, or not equals symbols, i.e., \((\neq, >, \text{or} <)\).
  • If we reject the null hypothesis, then we can assume there is enough evidence to support the alternative hypothesis.
  • Never state that a claim is proven true or false. Keep in mind the underlying fact that hypothesis testing is based on probability laws; therefore, we can talk only in terms of non-absolute certainties.

Formula Review

\(H_{0}\) and \(H_{a}\) are contradictory.

  • If \(\alpha \leq p\)-value, then do not reject \(H_{0}\).
  • If\(\alpha > p\)-value, then reject \(H_{0}\).

\(\alpha\) is preconceived. Its value is set before the hypothesis test starts. The \(p\)-value is calculated from the data.References

Data from the National Institute of Mental Health. Available online at http://www.nimh.nih.gov/publicat/depression.cfm .

Logo for UH Pressbooks

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

Hypothesis Testing with One Sample

Null and Alternative Hypotheses

OpenStaxCollege

[latexpage]

The actual test begins by considering two hypotheses . They are called the null hypothesis and the alternative hypothesis . These hypotheses contain opposing viewpoints.

H 0 : The null hypothesis: It is a statement about the population that either is believed to be true or is used to put forth an argument unless it can be shown to be incorrect beyond a reasonable doubt.

H a : The alternative hypothesis: It is a claim about the population that is contradictory to H 0 and what we conclude when we reject H 0 .

Since the null and alternative hypotheses are contradictory, you must examine evidence to decide if you have enough evidence to reject the null hypothesis or not. The evidence is in the form of sample data.

After you have determined which hypothesis the sample supports, you make a decision. There are two options for a decision. They are “reject H 0 ” if the sample information favors the alternative hypothesis or “do not reject H 0 ” or “decline to reject H 0 ” if the sample information is insufficient to reject the null hypothesis.

Mathematical Symbols Used in H 0 and H a :

H 0 always has a symbol with an equal in it. H a never has a symbol with an equal in it. The choice of symbol depends on the wording of the hypothesis test. However, be aware that many researchers (including one of the co-authors in research work) use = in the null hypothesis, even with > or < as the symbol in the alternative hypothesis. This practice is acceptable because we only make the decision to reject or not reject the null hypothesis.

H 0 : No more than 30% of the registered voters in Santa Clara County voted in the primary election. p ≤ 30

A medical trial is conducted to test whether or not a new medicine reduces cholesterol by 25%. State the null and alternative hypotheses.

H 0 : The drug reduces cholesterol by 25%. p = 0.25

H a : The drug does not reduce cholesterol by 25%. p ≠ 0.25

We want to test whether the mean GPA of students in American colleges is different from 2.0 (out of 4.0). The null and alternative hypotheses are:

H 0 : μ = 2.0

We want to test whether the mean height of eighth graders is 66 inches. State the null and alternative hypotheses. Fill in the correct symbol (=, ≠, ≥, <, ≤, >) for the null and alternative hypotheses.

  • H 0 : μ = 66
  • H a : μ ≠ 66

We want to test if college students take less than five years to graduate from college, on the average. The null and alternative hypotheses are:

H 0 : μ ≥ 5

We want to test if it takes fewer than 45 minutes to teach a lesson plan. State the null and alternative hypotheses. Fill in the correct symbol ( =, ≠, ≥, <, ≤, >) for the null and alternative hypotheses.

  • H 0 : μ ≥ 45
  • H a : μ < 45

In an issue of U. S. News and World Report , an article on school standards stated that about half of all students in France, Germany, and Israel take advanced placement exams and a third pass. The same article stated that 6.6% of U.S. students take advanced placement exams and 4.4% pass. Test if the percentage of U.S. students who take advanced placement exams is more than 6.6%. State the null and alternative hypotheses.

H 0 : p ≤ 0.066

On a state driver’s test, about 40% pass the test on the first try. We want to test if more than 40% pass on the first try. Fill in the correct symbol (=, ≠, ≥, <, ≤, >) for the null and alternative hypotheses.

  • H 0 : p = 0.40
  • H a : p > 0.40

<!– ??? –>

Bring to class a newspaper, some news magazines, and some Internet articles . In groups, find articles from which your group can write null and alternative hypotheses. Discuss your hypotheses with the rest of the class.

Chapter Review

In a hypothesis test , sample data is evaluated in order to arrive at a decision about some type of claim. If certain conditions about the sample are satisfied, then the claim can be evaluated for a population. In a hypothesis test, we:

Formula Review

H 0 and H a are contradictory.

If α ≤ p -value, then do not reject H 0 .

If α > p -value, then reject H 0 .

α is preconceived. Its value is set before the hypothesis test starts. The p -value is calculated from the data.

You are testing that the mean speed of your cable Internet connection is more than three Megabits per second. What is the random variable? Describe in words.

The random variable is the mean Internet speed in Megabits per second.

You are testing that the mean speed of your cable Internet connection is more than three Megabits per second. State the null and alternative hypotheses.

The American family has an average of two children. What is the random variable? Describe in words.

The random variable is the mean number of children an American family has.

The mean entry level salary of an employee at a company is 💲58,000. You believe it is higher for IT professionals in the company. State the null and alternative hypotheses.

A sociologist claims the probability that a person picked at random in Times Square in New York City is visiting the area is 0.83. You want to test to see if the proportion is actually less. What is the random variable? Describe in words.

The random variable is the proportion of people picked at random in Times Square visiting the city.

A sociologist claims the probability that a person picked at random in Times Square in New York City is visiting the area is 0.83. You want to test to see if the claim is correct. State the null and alternative hypotheses.

In a population of fish, approximately 42% are female. A test is conducted to see if, in fact, the proportion is less. State the null and alternative hypotheses.

Suppose that a recent article stated that the mean time spent in jail by a first–time convicted burglar is 2.5 years. A study was then done to see if the mean time has increased in the new century. A random sample of 26 first-time convicted burglars in a recent year was picked. The mean length of time in jail from the survey was 3 years with a standard deviation of 1.8 years. Suppose that it is somehow known that the population standard deviation is 1.5. If you were conducting a hypothesis test to determine if the mean length of jail time has increased, what would the null and alternative hypotheses be? The distribution of the population is normal.

A random survey of 75 death row inmates revealed that the mean length of time on death row is 17.4 years with a standard deviation of 6.3 years. If you were conducting a hypothesis test to determine if the population mean time on death row could likely be 15 years, what would the null and alternative hypotheses be?

  • H 0 : __________
  • H a : __________
  • H 0 : μ = 15
  • H a : μ ≠ 15

The National Institute of Mental Health published an article stating that in any one-year period, approximately 9.5 percent of American adults suffer from depression or a depressive illness. Suppose that in a survey of 100 people in a certain town, seven of them suffered from depression or a depressive illness. If you were conducting a hypothesis test to determine if the true proportion of people in that town suffering from depression or a depressive illness is lower than the percent in the general adult American population, what would the null and alternative hypotheses be?

Some of the following statements refer to the null hypothesis, some to the alternate hypothesis.

State the null hypothesis, H 0 , and the alternative hypothesis. H a , in terms of the appropriate parameter ( μ or p ).

  • The mean number of years Americans work before retiring is 34.
  • At most 60% of Americans vote in presidential elections.
  • The mean starting salary for San Jose State University graduates is at least 💲100,000 per year.
  • Twenty-nine percent of high school seniors get drunk each month.
  • Fewer than 5% of adults ride the bus to work in Los Angeles.
  • The mean number of cars a person owns in her lifetime is not more than ten.
  • About half of Americans prefer to live away from cities, given the choice.
  • Europeans have a mean paid vacation each year of six weeks.
  • The chance of developing breast cancer is under 11% for women.
  • Private universities’ mean tuition cost is more than 💲20,000 per year.
  • H 0 : μ = 34; H a : μ ≠ 34
  • H 0 : p ≤ 0.60; H a : p > 0.60
  • H 0 : μ ≥ 100,000; H a : μ < 100,000
  • H 0 : p = 0.29; H a : p ≠ 0.29
  • H 0 : p = 0.05; H a : p < 0.05
  • H 0 : μ ≤ 10; H a : μ > 10
  • H 0 : p = 0.50; H a : p ≠ 0.50
  • H 0 : μ = 6; H a : μ ≠ 6
  • H 0 : p ≥ 0.11; H a : p < 0.11
  • H 0 : μ ≤ 20,000; H a : μ > 20,000

Over the past few decades, public health officials have examined the link between weight concerns and teen girls’ smoking. Researchers surveyed a group of 273 randomly selected teen girls living in Massachusetts (between 12 and 15 years old). After four years the girls were surveyed again. Sixty-three said they smoked to stay thin. Is there good evidence that more than thirty percent of the teen girls smoke to stay thin? The alternative hypothesis is:

  • p < 0.30
  • p > 0.30

A statistics instructor believes that fewer than 20% of Evergreen Valley College (EVC) students attended the opening night midnight showing of the latest Harry Potter movie. She surveys 84 of her students and finds that 11 attended the midnight showing. An appropriate alternative hypothesis is:

  • p > 0.20
  • p < 0.20

Previously, an organization reported that teenagers spent 4.5 hours per week, on average, on the phone. The organization thinks that, currently, the mean is higher. Fifteen randomly chosen teenagers were asked how many hours per week they spend on the phone. The sample mean was 4.75 hours with a sample standard deviation of 2.0. Conduct a hypothesis test. The null and alternative hypotheses are:

  • H o : \(\overline{x}\) = 4.5, H a : \(\overline{x}\) > 4.5
  • H o : μ ≥ 4.5, H a : μ < 4.5
  • H o : μ = 4.75, H a : μ > 4.75
  • H o : μ = 4.5, H a : μ > 4.5

Data from the National Institute of Mental Health. Available online at http://www.nimh.nih.gov/publicat/depression.cfm.

Null and Alternative Hypotheses Copyright © 2013 by OpenStaxCollege is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

User Preferences

Content preview.

Arcu felis bibendum ut tristique et egestas quis:

  • Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris
  • Duis aute irure dolor in reprehenderit in voluptate
  • Excepteur sint occaecat cupidatat non proident

Keyboard Shortcuts

5.2 - writing hypotheses.

The first step in conducting a hypothesis test is to write the hypothesis statements that are going to be tested. For each test you will have a null hypothesis (\(H_0\)) and an alternative hypothesis (\(H_a\)).

When writing hypotheses there are three things that we need to know: (1) the parameter that we are testing (2) the direction of the test (non-directional, right-tailed or left-tailed), and (3) the value of the hypothesized parameter.

  • At this point we can write hypotheses for a single mean (\(\mu\)), paired means(\(\mu_d\)), a single proportion (\(p\)), the difference between two independent means (\(\mu_1-\mu_2\)), the difference between two proportions (\(p_1-p_2\)), a simple linear regression slope (\(\beta\)), and a correlation (\(\rho\)). 
  • The research question will give us the information necessary to determine if the test is two-tailed (e.g., "different from," "not equal to"), right-tailed (e.g., "greater than," "more than"), or left-tailed (e.g., "less than," "fewer than").
  • The research question will also give us the hypothesized parameter value. This is the number that goes in the hypothesis statements (i.e., \(\mu_0\) and \(p_0\)). For the difference between two groups, regression, and correlation, this value is typically 0.

Hypotheses are always written in terms of population parameters (e.g., \(p\) and \(\mu\)).  The tables below display all of the possible hypotheses for the parameters that we have learned thus far. Note that the null hypothesis always includes the equality (i.e., =).

  • Conjunctions
  • Prepositions

ALTERNATIVE HYPOTHESIS in a Sentence Examples: 21 Ways to Use Alternative Hypothesis

sentence with Alternative Hypothesis

Have you ever wondered about the alternative hypothesis in statistical analysis? In simple terms, the alternative hypothesis suggests a different outcome or relationship compared to the null hypothesis.

This hypothesis is a core concept in research, where it challenges the status quo and prompts further investigation to validate or reject its claims. Understanding the alternative hypothesis is crucial for drawing meaningful conclusions from data analysis in various fields of study.

Table of Contents

7 Examples Of Alternative Hypothesis Used In a Sentence For Kids

  • The alternative hypothesis helps us guess what might happen.
  • We can think of the alternative hypothesis as our special guess.
  • When we have an alternative hypothesis , we make a different kind of prediction.
  • The alternative hypothesis is like our creative idea about the experiment.
  • We use the alternative hypothesis to imagine other possibilities.
  • With the alternative hypothesis , we can explore different answers.
  • Let’s pretend with the alternative hypothesis and see what happens!

14 Sentences with Alternative Hypothesis Examples

  • Alternative hypothesis : The student council members proposed an alternative hypothesis for the decline in attendance during cultural events.
  • Have you considered including an alternative hypothesis in your research paper to provide a different perspective?
  • The debate team presented an alternative hypothesis on the effectiveness of social media activism.
  • The statistics class discussed how to properly formulate an alternative hypothesis for different experiments.
  • It is important for students to critically evaluate and test the alternative hypothesis before drawing conclusions.
  • The psychology professor encouraged the students to explore various alternative hypothesis in their case studies.
  • The economics group came up with an alternative hypothesis for the fluctuating prices of essential commodities.
  • In order to validate the initial findings, the science students need to test the proposed alternative hypothesis .
  • The literature review highlighted the significance of considering an alternative hypothesis to address the gaps in existing research.
  • As part of their project, the engineering students were tasked with formulating an alternative hypothesis to challenge the current design norms.
  • The marketing team suggested an alternative hypothesis for the decline in sales based on consumer behavior analysis.
  • By incorporating an alternative hypothesis in your project proposal, you can explore new avenues for investigation.
  • The sociology class was divided on which alternative hypothesis to pursue for their group project.
  • In order to enhance the validity of the results, the biology students need to propose an alternative hypothesis to test against the null hypothesis.

How To Use Alternative Hypothesis in Sentences?

To use the term Alternative Hypothesis in a sentence, start by introducing the main hypothesis being tested. Then, introduce the alternative hypothesis by stating the outcome or relationship that is being suggested as an alternative to the null hypothesis. For example, “The alternative hypothesis posits that there is a positive relationship between the amount of time spent studying and exam scores.”

It is important to remember that the alternative hypothesis is the statement you are trying to provide evidence for in a hypothesis test. This means you are looking for evidence to reject the null hypothesis in favor of the alternative hypothesis. When writing or discussing your research findings, be sure to clearly state the alternative hypothesis and explain how your data supports this hypothesis.

Furthermore, when using the term Alternative Hypothesis , make sure to distinguish it from the null hypothesis. The null hypothesis is the default assumption that there is no effect or relationship, while the alternative hypothesis suggests there is a significant effect or relationship. To effectively use the term in a sentence, highlight the difference between the two hypotheses and explain how they are being tested in your research.

By following these guidelines, beginners can confidently use the term Alternative Hypothesis in a sentence and understand its importance in hypothesis testing.

In scientific research, an alternative hypothesis is a statement that proposes there is a statistically significant difference or relationship between variables being studied. This hypothesis suggests that the results observed are not due to chance but are a reflection of a true effect present in the population. For example, “The data suggests that the new treatment improves patient outcomes,” is a sentence presenting an alternative hypothesis.

When conducting experiments or studies, researchers use the alternative hypothesis as a way to test their theories and determine if the results are indeed meaningful and support their proposed relationships. By formulating clear alternative hypotheses, scientists can make informed decisions based on data analysis and draw valid conclusions from their research findings.

Related Posts

In Front or Infront

In Front or Infront: Which Is the Correct Spelling?

As an expert blogger with years of experience, I’ve delved…  Read More » In Front or Infront: Which Is the Correct Spelling?

Targeted vs. Targetted

Targeted vs. Targetted: Correct Spelling Explained in English (US) Usage

Are you unsure about whether to use “targetted” or “targeted”?…  Read More » Targeted vs. Targetted: Correct Spelling Explained in English (US) Usage

As per Request or As per Requested

As per Request or As per Requested: Understanding the Correct Usage

Having worked in various office environments, I’ve often pondered the…  Read More » As per Request or As per Requested: Understanding the Correct Usage

example sentence of alternative hypothesis

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

  • Knowledge Base
  • Methodology
  • How to Write a Strong Hypothesis | Guide & Examples

How to Write a Strong Hypothesis | Guide & Examples

Published on 6 May 2022 by Shona McCombes .

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more variables . An independent variable is something the researcher changes or controls. A dependent variable is something the researcher observes and measures.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

Prevent plagiarism, run a free check.

Step 1: ask a question.

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2: Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalise more complex constructs.

Step 3: Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

Step 4: Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

  • The relevant variables
  • The specific group being studied
  • The predicted outcome of the experiment or analysis

Step 5: Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in if … then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

Step 6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis. The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

A hypothesis is not just a guess. It should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).

A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (‘ x affects y because …’).

A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses. In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

McCombes, S. (2022, May 06). How to Write a Strong Hypothesis | Guide & Examples. Scribbr. Retrieved 3 June 2024, from https://www.scribbr.co.uk/research-methods/hypothesis-writing/

Is this article helpful?

Shona McCombes

Shona McCombes

Other students also liked, operationalisation | a guide with examples, pros & cons, what is a conceptual framework | tips & examples, a quick guide to experimental design | 5 steps & examples.

Research Hypothesis In Psychology: Types, & Examples

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

A research hypothesis, in its plural form “hypotheses,” is a specific, testable prediction about the anticipated results of a study, established at its outset. It is a key component of the scientific method .

Hypotheses connect theory to data and guide the research process towards expanding scientific understanding

Some key points about hypotheses:

  • A hypothesis expresses an expected pattern or relationship. It connects the variables under investigation.
  • It is stated in clear, precise terms before any data collection or analysis occurs. This makes the hypothesis testable.
  • A hypothesis must be falsifiable. It should be possible, even if unlikely in practice, to collect data that disconfirms rather than supports the hypothesis.
  • Hypotheses guide research. Scientists design studies to explicitly evaluate hypotheses about how nature works.
  • For a hypothesis to be valid, it must be testable against empirical evidence. The evidence can then confirm or disprove the testable predictions.
  • Hypotheses are informed by background knowledge and observation, but go beyond what is already known to propose an explanation of how or why something occurs.
Predictions typically arise from a thorough knowledge of the research literature, curiosity about real-world problems or implications, and integrating this to advance theory. They build on existing literature while providing new insight.

Types of Research Hypotheses

Alternative hypothesis.

The research hypothesis is often called the alternative or experimental hypothesis in experimental research.

It typically suggests a potential relationship between two key variables: the independent variable, which the researcher manipulates, and the dependent variable, which is measured based on those changes.

The alternative hypothesis states a relationship exists between the two variables being studied (one variable affects the other).

A hypothesis is a testable statement or prediction about the relationship between two or more variables. It is a key component of the scientific method. Some key points about hypotheses:

  • Important hypotheses lead to predictions that can be tested empirically. The evidence can then confirm or disprove the testable predictions.

In summary, a hypothesis is a precise, testable statement of what researchers expect to happen in a study and why. Hypotheses connect theory to data and guide the research process towards expanding scientific understanding.

An experimental hypothesis predicts what change(s) will occur in the dependent variable when the independent variable is manipulated.

It states that the results are not due to chance and are significant in supporting the theory being investigated.

The alternative hypothesis can be directional, indicating a specific direction of the effect, or non-directional, suggesting a difference without specifying its nature. It’s what researchers aim to support or demonstrate through their study.

Null Hypothesis

The null hypothesis states no relationship exists between the two variables being studied (one variable does not affect the other). There will be no changes in the dependent variable due to manipulating the independent variable.

It states results are due to chance and are not significant in supporting the idea being investigated.

The null hypothesis, positing no effect or relationship, is a foundational contrast to the research hypothesis in scientific inquiry. It establishes a baseline for statistical testing, promoting objectivity by initiating research from a neutral stance.

Many statistical methods are tailored to test the null hypothesis, determining the likelihood of observed results if no true effect exists.

This dual-hypothesis approach provides clarity, ensuring that research intentions are explicit, and fosters consistency across scientific studies, enhancing the standardization and interpretability of research outcomes.

Nondirectional Hypothesis

A non-directional hypothesis, also known as a two-tailed hypothesis, predicts that there is a difference or relationship between two variables but does not specify the direction of this relationship.

It merely indicates that a change or effect will occur without predicting which group will have higher or lower values.

For example, “There is a difference in performance between Group A and Group B” is a non-directional hypothesis.

Directional Hypothesis

A directional (one-tailed) hypothesis predicts the nature of the effect of the independent variable on the dependent variable. It predicts in which direction the change will take place. (i.e., greater, smaller, less, more)

It specifies whether one variable is greater, lesser, or different from another, rather than just indicating that there’s a difference without specifying its nature.

For example, “Exercise increases weight loss” is a directional hypothesis.

hypothesis

Falsifiability

The Falsification Principle, proposed by Karl Popper , is a way of demarcating science from non-science. It suggests that for a theory or hypothesis to be considered scientific, it must be testable and irrefutable.

Falsifiability emphasizes that scientific claims shouldn’t just be confirmable but should also have the potential to be proven wrong.

It means that there should exist some potential evidence or experiment that could prove the proposition false.

However many confirming instances exist for a theory, it only takes one counter observation to falsify it. For example, the hypothesis that “all swans are white,” can be falsified by observing a black swan.

For Popper, science should attempt to disprove a theory rather than attempt to continually provide evidence to support a research hypothesis.

Can a Hypothesis be Proven?

Hypotheses make probabilistic predictions. They state the expected outcome if a particular relationship exists. However, a study result supporting a hypothesis does not definitively prove it is true.

All studies have limitations. There may be unknown confounding factors or issues that limit the certainty of conclusions. Additional studies may yield different results.

In science, hypotheses can realistically only be supported with some degree of confidence, not proven. The process of science is to incrementally accumulate evidence for and against hypothesized relationships in an ongoing pursuit of better models and explanations that best fit the empirical data. But hypotheses remain open to revision and rejection if that is where the evidence leads.
  • Disproving a hypothesis is definitive. Solid disconfirmatory evidence will falsify a hypothesis and require altering or discarding it based on the evidence.
  • However, confirming evidence is always open to revision. Other explanations may account for the same results, and additional or contradictory evidence may emerge over time.

We can never 100% prove the alternative hypothesis. Instead, we see if we can disprove, or reject the null hypothesis.

If we reject the null hypothesis, this doesn’t mean that our alternative hypothesis is correct but does support the alternative/experimental hypothesis.

Upon analysis of the results, an alternative hypothesis can be rejected or supported, but it can never be proven to be correct. We must avoid any reference to results proving a theory as this implies 100% certainty, and there is always a chance that evidence may exist which could refute a theory.

How to Write a Hypothesis

  • Identify variables . The researcher manipulates the independent variable and the dependent variable is the measured outcome.
  • Operationalized the variables being investigated . Operationalization of a hypothesis refers to the process of making the variables physically measurable or testable, e.g. if you are about to study aggression, you might count the number of punches given by participants.
  • Decide on a direction for your prediction . If there is evidence in the literature to support a specific effect of the independent variable on the dependent variable, write a directional (one-tailed) hypothesis. If there are limited or ambiguous findings in the literature regarding the effect of the independent variable on the dependent variable, write a non-directional (two-tailed) hypothesis.
  • Make it Testable : Ensure your hypothesis can be tested through experimentation or observation. It should be possible to prove it false (principle of falsifiability).
  • Clear & concise language . A strong hypothesis is concise (typically one to two sentences long), and formulated using clear and straightforward language, ensuring it’s easily understood and testable.

Consider a hypothesis many teachers might subscribe to: students work better on Monday morning than on Friday afternoon (IV=Day, DV= Standard of work).

Now, if we decide to study this by giving the same group of students a lesson on a Monday morning and a Friday afternoon and then measuring their immediate recall of the material covered in each session, we would end up with the following:

  • The alternative hypothesis states that students will recall significantly more information on a Monday morning than on a Friday afternoon.
  • The null hypothesis states that there will be no significant difference in the amount recalled on a Monday morning compared to a Friday afternoon. Any difference will be due to chance or confounding factors.

More Examples

  • Memory : Participants exposed to classical music during study sessions will recall more items from a list than those who studied in silence.
  • Social Psychology : Individuals who frequently engage in social media use will report higher levels of perceived social isolation compared to those who use it infrequently.
  • Developmental Psychology : Children who engage in regular imaginative play have better problem-solving skills than those who don’t.
  • Clinical Psychology : Cognitive-behavioral therapy will be more effective in reducing symptoms of anxiety over a 6-month period compared to traditional talk therapy.
  • Cognitive Psychology : Individuals who multitask between various electronic devices will have shorter attention spans on focused tasks than those who single-task.
  • Health Psychology : Patients who practice mindfulness meditation will experience lower levels of chronic pain compared to those who don’t meditate.
  • Organizational Psychology : Employees in open-plan offices will report higher levels of stress than those in private offices.
  • Behavioral Psychology : Rats rewarded with food after pressing a lever will press it more frequently than rats who receive no reward.

Print Friendly, PDF & Email

Related Articles

Qualitative Data Coding

Research Methodology

Qualitative Data Coding

What Is a Focus Group?

What Is a Focus Group?

Cross-Cultural Research Methodology In Psychology

Cross-Cultural Research Methodology In Psychology

What Is Internal Validity In Research?

What Is Internal Validity In Research?

What Is Face Validity In Research? Importance & How To Measure

Research Methodology , Statistics

What Is Face Validity In Research? Importance & How To Measure

Criterion Validity: Definition & Examples

Criterion Validity: Definition & Examples

Statology

Statistics Made Easy

How to Write a Null Hypothesis (5 Examples)

A hypothesis test uses sample data to determine whether or not some claim about a population parameter is true.

Whenever we perform a hypothesis test, we always write a null hypothesis and an alternative hypothesis, which take the following forms:

H 0 (Null Hypothesis): Population parameter =,  ≤, ≥ some value

H A  (Alternative Hypothesis): Population parameter <, >, ≠ some value

Note that the null hypothesis always contains the equal sign .

We interpret the hypotheses as follows:

Null hypothesis: The sample data provides no evidence to support some claim being made by an individual.

Alternative hypothesis: The sample data  does provide sufficient evidence to support the claim being made by an individual.

For example, suppose it’s assumed that the average height of a certain species of plant is 20 inches tall. However, one botanist claims the true average height is greater than 20 inches.

To test this claim, she may go out and collect a random sample of plants. She can then use this sample data to perform a hypothesis test using the following two hypotheses:

H 0 : μ ≤ 20 (the true mean height of plants is equal to or even less than 20 inches)

H A : μ > 20 (the true mean height of plants is greater than 20 inches)

If the sample data gathered by the botanist shows that the mean height of this species of plants is significantly greater than 20 inches, she can reject the null hypothesis and conclude that the mean height is greater than 20 inches.

Read through the following examples to gain a better understanding of how to write a null hypothesis in different situations.

Example 1: Weight of Turtles

A biologist wants to test whether or not the true mean weight of a certain species of turtles is 300 pounds. To test this, he goes out and measures the weight of a random sample of 40 turtles.

Here is how to write the null and alternative hypotheses for this scenario:

H 0 : μ = 300 (the true mean weight is equal to 300 pounds)

H A : μ ≠ 300 (the true mean weight is not equal to 300 pounds)

Example 2: Height of Males

It’s assumed that the mean height of males in a certain city is 68 inches. However, an independent researcher believes the true mean height is greater than 68 inches. To test this, he goes out and collects the height of 50 males in the city.

H 0 : μ ≤ 68 (the true mean height is equal to or even less than 68 inches)

H A : μ > 68 (the true mean height is greater than 68 inches)

Example 3: Graduation Rates

A university states that 80% of all students graduate on time. However, an independent researcher believes that less than 80% of all students graduate on time. To test this, she collects data on the proportion of students who graduated on time last year at the university.

H 0 : p ≥ 0.80 (the true proportion of students who graduate on time is 80% or higher)

H A : μ < 0.80 (the true proportion of students who graduate on time is less than 80%)

Example 4: Burger Weights

A food researcher wants to test whether or not the true mean weight of a burger at a certain restaurant is 7 ounces. To test this, he goes out and measures the weight of a random sample of 20 burgers from this restaurant.

H 0 : μ = 7 (the true mean weight is equal to 7 ounces)

H A : μ ≠ 7 (the true mean weight is not equal to 7 ounces)

Example 5: Citizen Support

A politician claims that less than 30% of citizens in a certain town support a certain law. To test this, he goes out and surveys 200 citizens on whether or not they support the law.

H 0 : p ≥ .30 (the true proportion of citizens who support the law is greater than or equal to 30%)

H A : μ < 0.30 (the true proportion of citizens who support the law is less than 30%)

Additional Resources

Introduction to Hypothesis Testing Introduction to Confidence Intervals An Explanation of P-Values and Statistical Significance

Featured Posts

7 Common Beginner Stats Mistakes and How to Avoid Them

Hey there. My name is Zach Bobbitt. I have a Masters of Science degree in Applied Statistics and I’ve worked on machine learning algorithms for professional businesses in both healthcare and retail. I’m passionate about statistics, machine learning, and data visualization and I created Statology to be a resource for both students and teachers alike.  My goal with this site is to help you learn statistics through using simple terms, plenty of real-world examples, and helpful illustrations.

2 Replies to “How to Write a Null Hypothesis (5 Examples)”

you are amazing, thank you so much

Say I am a botanist hypothesizing the average height of daisies is 20 inches, or not? Does T = (ave – 20 inches) / √ variance / (80 / 4)? … This assumes 40 real measures + 40 fake = 80 n, but that seems questionable. Please advise.

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Join the Statology Community

Sign up to receive Statology's exclusive study resource: 100 practice problems with step-by-step solutions. Plus, get our latest insights, tutorials, and data analysis tips straight to your inbox!

By subscribing you accept Statology's Privacy Policy.

IMAGES

  1. Alternative hypothesis

    example sentence of alternative hypothesis

  2. Alternative Hypothesis Example

    example sentence of alternative hypothesis

  3. Research Hypothesis Generator

    example sentence of alternative hypothesis

  4. 13 Different Types of Hypothesis (2024)

    example sentence of alternative hypothesis

  5. Examples of null hypothesis and an alternative hypothesis Archives

    example sentence of alternative hypothesis

  6. PPT

    example sentence of alternative hypothesis

VIDEO

  1. Two-Sample Hypothesis Testing: Dependent Sample

  2. Hypothesis Testing: the null and alternative hypotheses

  3. How to frame the Hypothesis statement in your Research

  4. Null Hypothesis vs Alternate Hypothesis

  5. Null Hypothesis vs Alternate Hypothesis

  6. Alternative hypothesis Meaning

COMMENTS

  1. Null & Alternative Hypotheses

    The null and alternative hypotheses are two competing claims that researchers weigh evidence for and against using a statistical test: Null hypothesis

  2. What is an Alternative Hypothesis in Statistics?

    This tutorial provides a simple explanation of an alternative hypothesis in statistics, including several examples.

  3. 17 Examples of an Alternative Hypothesis

    An alternative hypothesis is a hypothesis that there is a relationship between variables. This includes any hypothesis that predicts positive correlation, negative correlation, non-directional correlation or causation.

  4. Examples of null and alternative hypotheses

    The null and alternative hypotheses are both statements about the population that you are studying. The null hypothesis is often stated as the assumption that there is no change, no difference between two groups, or no relationship between two variables. The alternative hypothesis, on the other hand, is the statement that there is a change, difference, or relationship.

  5. Alternative Hypothesis

    An alternative hypothesis is a statement used in statistical testing that indicates the presence of an effect, relationship, or difference. It stands in direct contrast to the null hypothesis, which posits that there is no effect or relationship. The alternative causual hypothesis provides a specific direction to the research and can be directional (e.g., one value is greater than another) or ...

  6. Null and Alternative Hypotheses

    These hypotheses contain opposing viewpoints. H0: The null hypothesis: It is a statement about the population that either is believed to be true or is used to put forth an argument unless it can be shown to be incorrect beyond a reasonable doubt. Ha: The alternative hypothesis: It is a claim about the population that is contradictory to H0 and ...

  7. Null and Alternative Hypotheses

    The null and alternative hypotheses are two competing claims that researchers weigh evidence for and against using a statistical test: Null hypothesis (H0): There's no effect in the population. Alternative hypothesis (HA): There's an effect in the population. The effect is usually the effect of the independent variable on the dependent ...

  8. 9.1 Null and Alternative Hypotheses

    The actual test begins by considering two hypotheses. They are called the null hypothesis and the alternative hypothesis. These hypotheses contain oppos...

  9. Alternative Hypothesis-Definition, Types and Examples

    Alternative hypothesis is used to contradict the null hypothesis, in statistics. Learn its definition, types and the difference between the two hypotheses along with examples at BYJU'S.

  10. 8.1.1: Null and Alternative Hypotheses

    The actual test begins by considering two hypotheses. They are called the null hypothesis and the alternative hypothesis. These hypotheses contain opposing viewpoints. Since the null and alternative …

  11. Null and Alternative Hypotheses

    The actual test begins by considering two hypotheses. They are called the null hypothesis and the alternative hypothesis. These hypotheses contain opposing viewpoints.

  12. Alternative Hypothesis in Statistics

    Understand what an alternative hypothesis is and see alternative hypothesis examples. Learn how to write it and what is meant by ruling out the...

  13. 5.2

    5.2 - Writing Hypotheses. The first step in conducting a hypothesis test is to write the hypothesis statements that are going to be tested. For each test you will have a null hypothesis (\ (H_0\)) and an alternative hypothesis (\ (H_a\)). When writing hypotheses there are three things that we need to know: (1) the parameter that we are testing ...

  14. Alternative hypothesis

    The alternative hypothesis and null hypothesis are types of conjectures used in statistical tests, which are formal methods of reaching conclusions or making judgments on the basis of data. In statistical hypothesis testing, the null hypothesis and alternative hypothesis are two mutually exclusive statements.

  15. How to Write a Strong Hypothesis

    A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses.

  16. ALTERNATIVE HYPOTHESIS in a Sentence Examples: 21 Ways to Use

    To use the term Alternative Hypothesis in a sentence, start by introducing the main hypothesis being tested. Then, introduce the alternative hypothesis by stating the outcome or relationship that is being suggested as an alternative to the null hypothesis. For example, "The alternative hypothesis posits that there is a positive relationship ...

  17. Alternative Hypothesis

    The alternative hypothesis in research indicates a connection between the two variables in the study, that is, the dependent and independent variables. On the other hand, the null hypothesis asserts that there is no connection between them. An experimental hypothesis predicts what corresponding change (s) will occur in the dependent variable ...

  18. How to Write a Strong Hypothesis

    A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection.

  19. How to Write Hypothesis Test Conclusions (With Examples)

    To perform a hypothesis test in the real world, researchers obtain a random sample from the population and perform a hypothesis test on the sample data, using a null and alternative hypothesis: Null Hypothesis (H0): The sample data occurs purely from chance. Alternative Hypothesis (HA): The sample data is influenced by some non-random cause.

  20. Research Hypothesis In Psychology: Types, & Examples

    A research hypothesis, in its plural form "hypotheses," is a specific, testable prediction about the anticipated results of a study, established at its outset. The research hypothesis is often referred to as the alternative hypothesis.

  21. Null Hypothesis: Definition, Rejecting & Examples

    The null hypothesis in statistics states that there is no difference between groups or no relationship between variables. It is one of two mutually exclusive hypotheses about a population in a hypothesis test. When your sample contains sufficient evidence, you can reject the null and conclude that the effect is statistically significant.

  22. How to Write a Null Hypothesis (5 Examples)

    How to Write a Null Hypothesis (5 Examples) A hypothesis test uses sample data to determine whether or not some claim about a population parameter is true. Whenever we perform a hypothesis test, we always write a null hypothesis and an alternative hypothesis, which take the following forms: H0 (Null Hypothesis): Population parameter =, ≤, ≥ ...