What is hypothesis testing?

While hypothesis might make you think of science, hypothesis testing is a mathematical process that involves testing data using statistics to see if there is enough evidence to support a hypothesis. A hypothesis is a belief or a proposed explanation for something that has not yet been backed up by evidence. Hypothesis testing takes the data gathered in an experiment, survey, or other collection of information and interprets it. The five steps of hypothesis testing are specifying the null hypothesis (the statement of no relationship between the factors involved), specifying the alternative hypothesis (the statement that there is a relationship between the factors involved), setting the significance level (the percentage of chance the alternative hypothesis will be accepted), calculating the test statistic and corresponding P-value (probability of obtaining the sample statistic), and drawing a conclusion.

Why is hypothesis testing important to learn?

Learning hypothesis testing is important because it's what allows you to decide if something is true based on real data. If you're in marketing, for example, you can use hypothesis testing in consumer research to see how well your product is accepted by customers. If you're in the medical field, you can use it to see if a treatment has positive effects. An educational institution may be interested in determining if getting eight hours of sleep correlates with higher grades for its students. Hypothesis testing helps remove the likelihood of chance affecting a conclusion and instead backs it up with statistically significant data.

How can taking online courses on Coursera help me learn hypothesis testing?

Online courses on Coursera can help you learn how hypothesis testing applies to a variety of fields, including health care, business, artificial intelligence, psychology, social sciences, and machine learning. You can learn how to use specific statistical tools to conduct hypothesis testing, too, such as R, RStudio for Six Sigma, and Python. With online courses on Coursera, you also have the opportunity to learn the essential building blocks of hypothesis testing, which include choosing the right hypothesis testing tool and performing hypothesis tests using chi-square tests, correlation, t-tests, simple regression, logistic regression, and analysis of variance (ANOVA).

What are the benefits of taking an online Hypothesis Testing course?

Online Hypothesis Testing courses offer a convenient and flexible way to enhance your knowledge or learn new Hypothesis Testing skills. Choose from a wide range of Hypothesis Testing courses offered by top universities and industry leaders tailored to various skill levels.

What Hypothesis Testing courses are best for training and upskilling employees or the workforce?

When looking to enhance your workforce's skills in Hypothesis Testing, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here .

Best Hypothesis Testing Courses & Certificates [2025]

Explore the Hypothesis Testing Course Catalog

Johns Hopkins University
Hypothesis Testing in Public Health
Skills you'll gain: Biostatistics, Sampling (Statistics), Statistical Inference, Scientific Methods, Quantitative Research
4.8
Rating, 4.8 out of 5 stars
636 reviews
Beginner · Course · 1 - 3 Months
Rice University
Business Applications of Hypothesis Testing and Confidence Interval Estimation
Skills you'll gain: Statistical Hypothesis Testing, Sample Size Determination, Statistical Inference, Estimation, Business Analytics, Statistics, Probability & Statistics, Sampling (Statistics), Statistical Analysis, Microsoft Excel, Excel Formulas, Business, Data Analysis, Spreadsheet Software, Decision Making
4.8
Rating, 4.8 out of 5 stars
1.3K reviews
Mixed · Course · 1 - 4 Weeks
University of Colorado Boulder
Statistical Inference and Hypothesis Testing in Data Science Applications
Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Data Ethics, Sampling (Statistics), Probability & Statistics, Statistical Inference, Statistical Analysis, Quantitative Research, Probability Distribution
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
50 reviews
Intermediate · Course · 1 - 3 Months
Status: Free
Stanford University
Introduction to Statistics
Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Probability Distribution, Correlation Analysis
4.6
Rating, 4.6 out of 5 stars
4K reviews
Beginner · Course · 1 - 3 Months
Tufts University
Hypothesis Testing with Python and Excel
Skills you'll gain: Statistical Hypothesis Testing, Statistical Inference, Microsoft Excel, Quantitative Research, Probability & Statistics, Statistical Analysis, Sampling (Statistics), Data Analysis, Statistics, Business Analytics, Python Programming, Technical Communication
4.2
Rating, 4.2 out of 5 stars
23 reviews
Intermediate · Course · 1 - 4 Weeks
SAS
Introduction to Statistical Analysis: Hypothesis Testing
Skills you'll gain: Statistical Hypothesis Testing, Statistical Analysis, Correlation Analysis, SAS (Software), Regression Analysis, Statistical Methods, Probability & Statistics, Statistical Modeling, Plot (Graphics), Data Analysis, Analysis
4.7
Rating, 4.7 out of 5 stars
165 reviews
Intermediate · Course · 1 - 4 Weeks
Status: AI skills
IBM
IBM Full Stack Software Developer
Skills you'll gain: Istio, Node.JS, Software Development Life Cycle, Unit Testing, Object-Relational Mapping, Cloud Computing Architecture, Server Side, Application Deployment, React Redux, Kubernetes, Cloud Services, OpenShift, Git (Version Control System), Cloud Applications, Full-Stack Web Development, HTML and CSS, Cloud Computing, Jupyter, Generative AI, Interviewing Skills
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
54K reviews
Beginner · Professional Certificate · 3 - 6 Months
IBM
IBM AI Developer
Skills you'll gain: Generative AI, Software Development Life Cycle, Unit Testing, ChatGPT, HTML and CSS, Development Environment, Web Design and Development, Jupyter, Hypertext Markup Language (HTML), Software Engineering, Artificial Intelligence, Cascading Style Sheets (CSS), Web Development, Data Ethics, Application Deployment, Web Applications, Automation, Interviewing Skills, CI/CD, Professional Networking
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
66K reviews
Beginner · Professional Certificate · 3 - 6 Months
Coursera Project Network
RStudio for Six Sigma - Hypothesis Testing
Skills you'll gain: Statistical Hypothesis Testing, Correlation Analysis, Six Sigma Methodology, R Programming, Statistical Analysis, Statistical Methods, Regression Analysis, Probability & Statistics, Data Analysis
4.5
Rating, 4.5 out of 5 stars
10 reviews
Intermediate · Guided Project · Less Than 2 Hours
Google
The Power of Statistics
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Descriptive Statistics, Data Analysis, Statistical Analysis, Probability Distribution, Statistical Methods, Statistics, Statistical Inference, Probability, Bayesian Statistics, Statistical Programming, A/B Testing
4.8
Rating, 4.8 out of 5 stars
763 reviews
Advanced · Course · 1 - 3 Months
Duke University
Inferential Statistics
Skills you'll gain: Statistical Hypothesis Testing, Statistical Inference, Statistical Reporting, Statistical Methods, R Programming, Statistical Software, Statistical Analysis, Probability & Statistics, Data Analysis, Sampling (Statistics), Probability Distribution, Software Installation
4.8
Rating, 4.8 out of 5 stars
2.7K reviews
Beginner · Course · 1 - 3 Months
IBM
Exploratory Data Analysis for Machine Learning
Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Data Cleansing, Data Access, Data Analysis, Statistical Inference, Statistical Hypothesis Testing, Data Quality, Probability & Statistics, Jupyter, Big Data, Machine Learning, Data Manipulation, Pandas (Python Package), Statistical Analysis, Data Transformation, Data Presentation, Artificial Intelligence
4.6
Rating, 4.6 out of 5 stars
2.2K reviews
Intermediate · Course · 1 - 3 Months