Type I And Type II Errors

Question 1

What is the null hypothesis?

Answer 1

The null hypothesis (H0) states there is no significance.

Question 2

What is the alternative hypothesis?

Answer 2

The experimental or alternative hypothesis suggests significance.

Question 3

What is a Type I error?

Answer 3

A Type I error occurs when the null hypothesis is rejected when it is actually true (false positive).

Question 4

What is a Type II error?

Answer 4

A Type II error occurs when the null hypothesis is accepted when it is actually false (false negative).

Question 5

What is the significance level p = 0.05?

Answer 5

A significance level of p = 0.05 indicates a 5% probability of making a Type I error.

Question 6

What does a significance level of P ≤ 0.15 indicate?

Answer 6

A significance level of P ≤ 0.15 indicates a higher likelihood of making a Type I error (10% chance results due to chance).

Question 7

What does a significance level of P ≤ 0.01 indicate?

Answer 7

A significance level of P ≤ 0.01 indicates a higher likelihood of making a Type II error (1% chance results due to chance).

Question 8

What is a consequence of a 0.01 significance level?

Answer 8

A 0.01 significance level may lead to a Type I error due to the 1% probability that the null hypothesis is correct.

Question 9

What is one way to check for a Type II error?

Answer 9

One way to check for a Type II error is by repeating the experiment and comparing the findings.

Question 10

Fill in the blank: A Type I error is considered too _______.

Answer 10

[lenient]

Question 11

Fill in the blank: A Type II error is considered too _______.

Answer 11

[strict]