Statistics for Data Science and Business Analysis - Type I Error Versus Type II Error

What is a Type I error in hypothesis testing?

• Accepting a true null hypothesis

• Accepting a false null hypothesis

• Rejecting a true null hypothesis

• Rejecting a false null hypothesis

Which factor primarily influences the probability of making a Type II error?

• Researcher's bias

• Sample size

• Number of variables

• Level of significance

What does the power of a test refer to in hypothesis testing?

• The probability of rejecting a false null hypothesis

• The probability of accepting a true null hypothesis

• The probability of making a Type II error

• The probability of making a Type I error

In the given example, what is the consequence of making a Type I error?

• You invite her out and she accepts

• You do nothing and miss an opportunity

• You invite her out and face rejection

• You accept the status quo and remain friends

In the romantic example, what happens if you make a Type II error?

• You accept the status quo and remain friends

• You invite her out and face rejection

• You do nothing and miss an opportunity

• You invite her out and she accepts