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    Hypothesis Testing Courses Online

    Study hypothesis testing for statistical analysis. Learn to formulate and test hypotheses using various statistical methods.

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    Explore the Hypothesis Testing Course Catalog

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Statistical Inference and Hypothesis Testing in Data Science Applications

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Probability & Statistics, Data Ethics, Statistical Analysis, Quantitative Research, Statistical Inference, Statistics, Sample Size Determination, Sampling (Statistics)

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      50 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Hypothesis Testing in Public Health

      Skills you'll gain: Statistical Hypothesis Testing, Biostatistics, Sampling (Statistics), Statistical Inference, Scientific Methods, Quantitative Research, Public Health

      4.8
      Rating, 4.8 out of 5 stars
      ·
      646 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      R

      Rice University

      Business Applications of Hypothesis Testing and Confidence Interval Estimation

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Sample Size Determination, Statistical Inference, Estimation, Statistics, Probability & Statistics, Sampling (Statistics), Statistical Analysis, Microsoft Excel, Excel Formulas, Data Analysis, Decision Making

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.3K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      S

      SAS

      Introduction to Statistical Analysis: Hypothesis Testing

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Analysis, Correlation Analysis, SAS (Software), Regression Analysis, Exploratory Data Analysis, Statistical Methods, Probability & Statistics, Statistical Modeling, Plot (Graphics), Data Literacy

      4.7
      Rating, 4.7 out of 5 stars
      ·
      170 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google

      The Power of Statistics

      Skills you'll gain: Sampling (Statistics), Descriptive Statistics, Statistical Hypothesis Testing, Data Analysis, Probability Distribution, Statistics, Data Science, Statistical Analysis, A/B Testing, Statistical Methods, Probability, Statistical Inference, Statistical Programming, Python Programming, Technical Communication

      4.8
      Rating, 4.8 out of 5 stars
      ·
      835 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Probability & Statistics for Machine Learning & Data Science

      Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Statistical Inference, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Exploratory Data Analysis, Statistical Visualization

      4.6
      Rating, 4.6 out of 5 stars
      ·
      600 reviews

      Intermediate · Course · 1 - 4 Weeks

    What brings you to Coursera today?

    • Status: Free Trial
      Free Trial
      M

      Meta

      Statistics Foundations

      Skills you'll gain: Bayesian Statistics, Descriptive Statistics, Statistical Hypothesis Testing, Statistical Inference, Sampling (Statistics), Data Modeling, Statistics, Probability & Statistics, Statistical Analysis, Statistical Methods, Statistical Modeling, Marketing Analytics, Tableau Software, Data Analysis, Spreadsheet Software, Analytics, Time Series Analysis and Forecasting, Regression Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      356 reviews

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      Status: Preview
      Preview
      C

      Coursera

      Beyond basics: Advanced Data Analysis with Python

      Skills you'll gain: A/B Testing, Statistical Hypothesis Testing, Statistical Methods, Advanced Analytics, Statistical Analysis, Correlation Analysis, Business Reporting, Data Analysis, Report Writing, Probability & Statistics, Analytical Skills, Quantitative Research, Data-Driven Decision-Making, Health Informatics, Business Process Automation

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Amsterdam

      Basic Statistics

      Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Statistics, Statistical Analysis, Histogram, R Programming, Scatter Plots

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.6K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Preview
      Preview
      S

      Stanford University

      Introduction to Statistics

      Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Probability Distribution

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.2K reviews

      Beginner · Course · 1 - 3 Months

    • D

      Duke University

      Bayesian Statistics

      Skills you'll gain: Bayesian Statistics, Statistical Hypothesis Testing, Statistical Modeling, Statistical Methods, Statistical Inference, Regression Analysis, Data Analysis, R Programming, Probability, Predictive Modeling, Probability Distribution

      3.8
      Rating, 3.8 out of 5 stars
      ·
      798 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      C

      Coursera Instructor Network

      Advanced Quantitative Statistics with Excel

      Skills you'll gain: Regression Analysis, Microsoft Excel, Statistical Hypothesis Testing, Business Analytics, Data-Driven Decision-Making, Data Visualization, Business Analysis, Statistical Analysis, Statistical Methods, Analytics, Spreadsheet Software, Data Analysis, Data Analysis Software, Correlation Analysis, Case Studies, Probability & Statistics, Variance Analysis, Forecasting, Data Manipulation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      9 reviews

      Beginner · Course · 1 - 4 Weeks

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    In summary, here are 10 of our most popular hypothesis testing courses

    • Statistical Inference and Hypothesis Testing in Data Science Applications: University of Colorado Boulder
    • Hypothesis Testing in Public Health : Johns Hopkins University
    • Business Applications of Hypothesis Testing and Confidence Interval Estimation : Rice University
    • Introduction to Statistical Analysis: Hypothesis Testing: SAS
    • The Power of Statistics: Google
    • Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
    • Statistics Foundations: Meta
    • Beyond basics: Advanced Data Analysis with Python: Coursera
    • Basic Statistics: University of Amsterdam
    • Introduction to Statistics: Stanford University

    Frequently Asked Questions about 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.‎

    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.‎

    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).‎

    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.‎

    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.‎

    Automated hypothesis testing uses algorithms to generate, run, and evaluate statistical tests at scale—often in A/B testing, analytics, or scientific research. It reduces manual effort and speeds up decision-making using tools like Python, R, or specialized platforms. Courses like Statistics with Python from the University of Michigan on Coursera cover the foundations needed to apply automated testing methods.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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