Imagine betting big on a result, only to find out it’s all smoke and mirrors. That’s a Type I error in stats. Now, picture the opposite: Ignoring a hidden gem because it didn't shine brightly enough—that's a Type II error.

These statistical missteps can alter outcomes dramatically.

Want to avoid them? This episode will help you understand how to navigate these errors effectively.

Here is what’s in store for you in this podcast:

I'll tell you what the Type I and Type II errors are

Where they belong in statistics

How to distinguish between them

How to minimize them

TIMESTAMPS

Type One Error Explained (00:01:26)

Introduction to Type One error, a false positive, illustrated with a pregnancy test example.

Type Two Error Explained (00:02:42)

Discussion of Type Two error, a false negative, with the missed detection of pregnancy as an example.

Factors Contributing to Errors (00:03:52)

Exploration of various factors that can lead to statistical errors in hypothesis testing.

Example of Social Media Impact Study (00:05:03)

Illustration of Type One and Type Two errors using a study on social media's effect on self-esteem.

Minimizing Type One and Type Two Errors (00:06:10)

Advice on how to reduce Type One and Type Two errors through significance levels and sample size.

Summary of Type One and Type Two Errors (00:09:53)

Recap of the definitions and differences between Type One and Type Two errors.

Closing Remarks and Resources (00:11:02)

Melanie encourages listeners to subscribe and offers a free cheat sheet for the independent samples t-test.

LINKS:

TRANSCRIPT

https://statisticssimplyexplained.com/wp-content/uploads/2024/08/PC-03_-What-are-Type-1-and-2-Errors_.pdf

WAITING LIST ONLINE COURSE “HYPOTHESIS TESTING MADE EASY!”

https://statisticssimplyexplained.com/waiting-list-hypothesis-testing-made-easy/

CHEAT SHEET FOR THE INDEPENDENT SAMPLES t-TEST

https://statisticssimplyexplained.com/cheat-sheet-t-test/