Hypothesis Testing

Front

What is the null hypothesis (H0)?

Back

The null hypothesis (H0) is a statement that there is no effect or no difference, and it serves as the default assumption in hypothesis testing.

Front

What is the alternative hypothesis (Ha)?

Back

The alternative hypothesis (Ha) is a statement that indicates the presence of an effect or a difference, opposing the null hypothesis.

Front

What does a P-value represent in hypothesis testing?

Back

The P-value represents the probability of obtaining test results at least as extreme as the observed results, assuming that the null hypothesis is true.

Front

What does it mean to reject the null hypothesis?

Back

Rejecting the null hypothesis means that there is sufficient evidence to support the alternative hypothesis.

Front

What does it mean to fail to reject the null hypothesis?

Back

Failing to reject the null hypothesis means that there is not enough evidence to support the alternative hypothesis.

Front

What is a Type I error?

Back

A Type I error occurs when the null hypothesis is true, but is incorrectly rejected.

Front

What is a Type II error?

Back

A Type II error occurs when the null hypothesis is false, but is incorrectly failed to be rejected.

Front

What is the significance level (α) in hypothesis testing?

Back

The significance level (α) is the threshold for determining whether to reject the null hypothesis, commonly set at 0.05 or 0.01.

Front

How do you interpret a P-value less than α?

Back

If the P-value is less than α, you reject the null hypothesis, indicating that the results are statistically significant.

Front

How do you interpret a P-value greater than α?

Back

If the P-value is greater than α, you fail to reject the null hypothesis, indicating that the results are not statistically significant.