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?

Evaluate responses using AI:

OFF

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

Evaluate responses using AI:

OFF

Explain the difference between type I and type II errors.

Evaluate responses using AI:

OFF

How can researchers control the rate of type I errors?

Evaluate responses using AI:

OFF

How do researchers estimate the alternative distribution when testing hypotheses?

Evaluate responses using AI:

OFF

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

Evaluate responses using AI:

OFF

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

Evaluate responses using AI:

OFF

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

Evaluate responses using AI:

OFF

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

Evaluate responses using AI:

OFF

Describe how sample size affects statistical power.

Evaluate responses using AI:

OFF