Pre-Assessment: Hypothesis Testing

Test your baseline knowledge before starting the module

About This Assessment

This 5-question assessment measures what you already know about hypothesis testing before you start learning. Don't worry if you don't know the answers—that's the point!

This is not graded and doesn't affect your course progress
Answer based on your current understanding
It's okay to guess if you're unsure
You'll retake this at the end to measure your learning gains

Question 1

What is the purpose of hypothesis testing?

To prove that a hypothesis is true
To determine if there is enough evidence to reject a null hypothesis
To calculate the exact value of a population parameter
To create confidence intervals

Question 2

The null hypothesis (H₀) typically represents:

The alternative claim we want to prove
The status quo or claim of no effect
The research hypothesis
A hypothesis that is always false

Question 3

A Type I error occurs when:

We reject a true null hypothesis
We fail to reject a false null hypothesis
We calculate the test statistic incorrectly
We use the wrong significance level

Question 4

If a p-value is 0.03 and the significance level (α) is 0.05, we should:

Fail to reject the null hypothesis
Reject the null hypothesis
Accept the alternative hypothesis
Increase the sample size

Question 5

When testing a claim about a population mean with unknown population standard deviation, which test should you use?

z-test
t-test
chi-square test
ANOVA

Pre-Assessment Complete!

What This Score Means

Remember, this is a baseline measurement. Whether you scored high or low, you're about to learn a lot in this module!

Next steps:

Your score has been recorded (for research purposes only)
Start with Lesson 1 to learn the fundamentals of hypothesis testing
After completing the module, you'll retake this assessment to see your improvement

Start Lesson 1 → Back to Module Home