Independent T-test TRUE or FALSE

An independent t-test can be used to compare the means of two related groups (e.g., students before and after an intervention).

• TRUE

• FALSE

Answer explanation

FALSE - Independent t-tests are for comparing independent groups, not related ones.

A statistically significant p-value in an independent t-test always guarantees a large difference between the means of the two groups.

• TRUE

• FALSE

Answer explanation

FALSE - A significant p-value only tells us the observed difference is unlikely due to chance, not necessarily a large difference.

The independent t-test assumes the data from both groups being compared follows a normal distribution.

• TRUE

• FALSE

Answer explanation

TRUE - The independent t-test has an assumption of normality for the data in both groups.

A larger sample size will always lead to a more significant p-value in an independent t-test.

• TRUE

• FALSE

Answer explanation

FALSE - A larger sample size will generally lead to a smaller p-value, making it easier to reject the null hypothesis, even for small differences.

The independent t-test can be used to compare more than two groups at the same time.

• TRUE

• FALSE

Answer explanation

FALSE - The independent t-test is specifically designed for comparing the means of two independent groups.

Imagine you are a researcher interested in the impact of social media use on sleep quality. You design a study where you recruit 100 volunteers and randomly assign them to two groups:

·  Group 1 (Control): Instructed to avoid social media for one hour before bedtime for two weeks.

·  Group 2 (social media): No restrictions on social media use before bedtime for two weeks.

After the two-week period, you collect data on their self-reported sleep quality using a standardized sleep scale.

Question: Discuss the limitations of using an independent t-test in this specific study.