Hypothesis Testing Courses and Certifications

Hypothesis Testing in Python

3678 ratings at DataCamp

Hypothesis testing lets you answer questions about your datasets in a statistically rigorous way.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Hypothesis Testing in R

1033 ratings at DataCamp

Discover Hypothesis Testing in R Hypothesis testing lets you ask questions about your datasets and answer them in a statistically rigorous way.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Hypothesis Testing

Learn to use statistical inference, confidence intervals, hypothesis testing, and A/B tests to evaluate experiments with Python.

• Udacity
• 21 hours
• Self-Paced
• Paid Course

Hypothesis Testing in R

Learn to perform and interpret t-tests, Mann-Whitney U tests, ANOVA, and chi-square tests in R for data-driven decisions.

• CodeSignal
• 2 hours
• Self-Paced
• Free Certificate

Hypothesis Testing

Unlock the power of data-driven decision-making with hypothesis testing!

• OpenLearning
• 20 hours
• Self-Paced
• Paid Course

Hypothesis Testing with Python

1 rating

Run t-tests, Mann-Whitney U tests, one-way ANOVA, and chi-square tests in Python, interpreting t-statistics and p-values to draw data-driven conclusions.

• CodeSignal
• 1 hour
• Self-Paced
• Free Certificate

Hypothesis Testing in Public Health

661 ratings at Coursera

Evaluate sample variability and test hypotheses with published health data: sampling distributions, the central limit theorem, confidence intervals, p values, and comparisons of means, proportions, and rates.

• Coursera
• 6 weeks, 3 hours a week
• Self-Paced
• Paid Course

Business Applications of Hypothesis Testing and Confidence Interval Estimation

1338 ratings at Coursera

Construct confidence intervals and run hypothesis tests in Excel: t- and z-statistics, population proportions, sample size calculation, Type I/II errors, and difference-in-means tests.

• Coursera
• 4 weeks, 6 hours a week
• Self-Paced
• Paid Course

Data Science Decisions in Time:Sequential Hypothesis Testing

Extend Chernoff's sequential hypothesis testing to active hypothesis selection: build biased tree walks, scale to large action spaces, and apply results to MRI and protein design.

• Coursera
• 6 weeks, 4 hours a week
• Self-Paced
• Paid Course

Statistical Inference and Hypothesis Testing in Data Science Applications

55 ratings at Coursera

Design and interpret hypothesis tests: null and alternative hypotheses, power functions, p-values, t- and two-sample tests, uniformly most powerful tests, likelihood ratio and chi-squared tests.

• Coursera
• 6 weeks, 6 hours a week
• Self-Paced
• Paid Course

BiteSize Stats: Hypothesis Testing for Single Samples

Learn to test single-sample claims using p-values, one-sample Z- and t-tests, chi-square goodness-of-fit, confidence intervals, and power-based sample-size planning.

• Coursera
• 5 weeks, 15 hours a week
• Self-Paced
• Paid Course

BiteSize Stats: Hypothesis Testing for Two Samples

Compare business groups using two-sample Z- and t-tests, paired t-tests, proportion tests, chi-square independence tests, and one-way ANOVA with Tukey’s HSD.

• Coursera
• 5 weeks, 16 hours a week
• Self-Paced
• Paid Course

Introduction to Statistical Analysis: Hypothesis Testing

176 ratings at Coursera

This introductory course is for SAS software users who perform statistical analyses using SAS/STAT software. The focus is on t tests, ANOVA, and linear regression, and includes a brief introduction to logistic regression.

• Coursera
• 3 weeks, 3 hours a week
• Self-Paced
• Paid Course

Tufts University

Hypothesis Testing with Python and Excel

24 ratings at Coursera

Test hypotheses about a population mean and proportion using Excel and Python, apply the central limit theorem, and plan a workplace experiment.

• Coursera
• 5 hours 14 minutes
• Self-Paced
• Paid Course

Coursera

RStudio for Six Sigma - Hypothesis Testing

14 ratings at Coursera

Perform hypothesis tests hands-on in RStudio: correlation, simple and logistic regression, chi-square, t-tests, ANOVA, and non-parametric Wilcoxon Rank Sum and Kruskal-Wallis tests.

• Coursera
• 2 hours 10 minutes
• Self-Paced
• Paid Course