Module 8: Hypothesis Testing
Learn how to test claims about populations using statistical methods. Master the logic of hypothesis testing, understand Type I and Type II errors, and conduct tests for means and proportions.
Your Progress
Learning Objectives
By the end of this module, you will be able to:
- Formulate null and alternative hypotheses for research questions
- Explain the logic and steps of hypothesis testing
- Distinguish between Type I and Type II errors and understand statistical power
- Conduct z-tests and t-tests for population means
- Perform hypothesis tests for population proportions
- Interpret p-values and make decisions using both critical value and p-value approaches
Why This Matters
Hypothesis testing is the backbone of scientific research! From medical trials to quality control, from marketing campaigns to social science research, hypothesis testing helps us make evidence-based decisions.
This module gives you the tools to:
- Evaluate scientific claims with statistical rigor
- Understand research findings in academic papers
- Make data-driven decisions in business and policy
- Critically assess statistical claims in the media
- Design and analyze your own research studies
Prerequisites
What You Need to Know First
This module builds directly on previous concepts. Make sure you understand:
- Module 5: Normal Distribution and z-scores
- Module 6: Sampling Distributions and Central Limit Theorem
- Module 7: Confidence Intervals and Margin of Error
If you need to review, go back to those modules before starting this one. Hypothesis testing will make much more sense with a solid foundation!
Get Started: Pre-Assessment
Before You Begin...
Take a quick 5-question pre-assessment to see what you already know about hypothesis testing. This isn't graded—it's just to establish your baseline knowledge.
Why do this? At the end of the module, you'll retake the same assessment and measure your learning gains!
Recommended: Take the pre-assessment! It helps you see how much you learn.
Module Lessons
Introduction to Hypothesis Testing
Learn the logic of hypothesis testing, how to formulate null and alternative hypotheses, and the steps of the hypothesis testing process. Understand one-tailed vs. two-tailed tests.
30-35 minutes
Type I and Type II Errors & Power
Understand the two types of errors in hypothesis testing, their consequences, and the concept of statistical power. Learn the tradeoffs between α and β.
25-30 minutes
Hypothesis Tests for Means
Master z-tests and t-tests for population means. Learn when to use each test, how to calculate test statistics, and how to make decisions using both critical value and p-value approaches.
35-40 minutes
Hypothesis Tests for Proportions
Learn how to test claims about population proportions. Understand the conditions for valid tests and apply hypothesis testing to real-world scenarios like quality control and survey data.
30-35 minutes
After the Lessons
Practice Problems
Apply what you've learned with 20 comprehensive practice problems covering all hypothesis testing concepts. Detailed solutions included!
Practice ProblemsModule Quiz
Test your mastery with a 15-question quiz. Pass with 70% to earn your Module 8 badge!
Take Module QuizStudy Materials
Download printable study guides and quick reference cards with all formulas and decision rules. Perfect for exam prep!
AI Tutor Help
Stuck on hypothesis testing? Chat with the AI statistics tutor for personalized guidance and step-by-step help.
Get AI HelpTips for Success
- Master the logic first - Understand WHY we do hypothesis testing before worrying about calculations.
- Practice identifying hypotheses - Setting up H₀ and Hₐ correctly is crucial for everything else.
- Know when to use which test - Create a flowchart to decide between z-test and t-test.
- Interpret in context - Always relate your statistical conclusion back to the real-world question.
- Don't confuse "fail to reject" with "accept" - This is a common mistake that can change your interpretation!