Playing with Power P-Values Pt 3 - Crash Course Statistics

The video explores null hypothesis testing, focusing on p values and decision-making. It explains Type I and Type II errors, highlighting their implications and trade-offs. The concept of statistical power is introduced, emphasizing its role in detecting effects in experiments. The video concludes with a discussion on the importance of sample size and effect size in achieving sufficient statistical power.

What is the null hypothesis and how does it relate to significance testing?

What does a low p-value indicate in hypothesis testing?

Explain the difference between type I and type II errors.

How can researchers control the rate of type I errors?

How do researchers estimate the alternative distribution when testing hypotheses?

In what situations might a type I error be preferable to a type II error?

What is statistical power and why is it important in hypothesis testing?

What are the implications of having a high overlap between null and alternative distributions?

What is effect size and how does it relate to the null and alternative hypotheses?

Describe how sample size affects statistical power.