21 Effect Size

Question 1

What is the definition of Effect Size?

Answer 1

Quantifying the relationship between two groups

Effect size is important for understanding the magnitude of differences, not just statistical significance.

Question 2

What is Cohen’s d used for?

Answer 2

Measuring the size of the difference between two groups

It expresses the difference in standard deviation units.

Question 3

True or false: A hypothesis test measures the size of an effect.

Answer 3

FALSE

A hypothesis test detects if there is an effect but does not indicate how large the effect is.

Question 4

What does a larger sample size affect in hypothesis testing?

Answer 4

• Can result in a significant p-value
• May lead to non-rejection of the null hypothesis with low power

Larger sample sizes can lead to more reliable results but do not directly influence effect size.

Question 5

True or false: A hypothesis test measures the size of an effect.

Answer 5

FALSE

A hypothesis test detects if there is an effect but does not indicate how large the effect is.

Question 6

True or false: Effect size measures the size of an effect.

Answer 6

TRUE

Question 7

What does Cohen’s d indicate when it equals 1?

Answer 7

The two groups differ by 1 standard deviation

A d of 2 indicates a difference of 2 standard deviations, and so forth.

Question 8

What is the formula for Cohen’s d?

Answer 8

This formula helps quantify the effect size between two groups.

Question 9

What are the general guidelines for interpreting effect sizes according to Cohen?

Answer 9

• SMALL effect size: d < 0.2
• MEDIUM effect size: d ≈ 0.5
• LARGE effect size: d > 0.8

These guidelines should be used cautiously when interpreting results.

Question 10

What is the relationship between effect size and sample size?

Answer 10

Effect size is not directly influenced by sample size

Changes in sample size do not translate to meaningful changes in effect size.

Question 11

Fill in the blank: A p-value tells us whether there is a statistically significant difference, while an __________ tells us how large this difference actually is.

Answer 11

Effect Size

Effect sizes provide more context than p-values alone.

Question 12

What is the importance of considering effect size together with p-value?

Answer 12

It provides a more comprehensive understanding of the results

Relying solely on p-values can be misleading.

Question 13

In the context of effect size, what does a negative value of Cohen’s d indicate?

Answer 13

This is same effect as the equivalent positive Cohen’s d value.

The value means the first group has a lower mean than the second.

Question 14

What does a p-value represent in hypothesis testing?

Answer 14

The probability of observing the test statistic under the null hypothesis

It helps determine whether to reject the null hypothesis.

Question 15

What is the critical region in hypothesis testing?

Answer 15

The area where the test statistic would lead to rejection of the null hypothesis

It is determined based on the significance level.

Question 16

What four cases can occur with hypothesis test results and the Cohen’s d value?

Answer 16

• Case 1 test result statistically significant with a large effect size;
• Case 2 test result statistically significant with a small effect size;
• Case 3 test result not statistically significant but a large effect size;
• Case 4 test result not statistically significant but a small effect size.