Equality of Means (t-test)

Question 1

What are the three t-tests?

Answer 1

▪️One sample
▪️Independent samples
▪️Paired sampled

Question 2

When would you used a one sample t-test?

Answer 2

To test is the mean of the population differs from a pre-specified test value?

E.g. difference between average height of your class and known average height of children

Question 3

When would you used an independent t-test?

Answer 3

To study the difference in means between two groups

E.g. Healthy OA vs MCI

Question 4

When might you used a paired sames t-test?

Answer 4

To study the difference in means of the same group.

E.g. before and after treatment, matched case controls

Question 5

For a t-test, the variable whose mean is tested needs to be _____________________

Answer 5

Fairly symmetrical (bell shaped)

Question 6

What can you use to check whether your data is symmetrical/normal enough?

Answer 6

A normality test (e.g. Kolmogorov-Smirnov test)

Non-parametric –> Legacy dialogs –> K-S

Question 7

What is the null hypothesis of a normality test?

Answer 7

There is no difference between your data and normality

Question 8

What is the main problem with normality tests?

Answer 8

They tend to be very conservative, especially when the sample size is large

Question 9

The ____________ the sample size, the more likely the K-S test is to tell you the data is not symmetrical.

Answer 9

Larger

Question 10

What test would you used to test whether the population mean is equal to a certain value?

Answer 10

One sample t-test

Question 11

What assumptions are made for the one sample t-test?

Answer 11

▪️The observations are randomly and independently drawn
▪️Symmetrical, bell-shaped data (normal)
▪️There are no outliers

Question 12

What test would you use to see whether the mean of group A is equal to the mean group B?

Answer 12

Independent samples t-test

Question 13

What is the df of a one sample t-test?

Answer 13

n-1

Question 14

What is the df for an independent samples t-test?

Answer 14

nA + nB - 2

Question 15

What assumptions are made for independent samples t-test?

Answer 15

▪️The observations are randomly and independently drawn
▪️Symmetrical within each group
▪️No outliers within each group

Question 16

What must you do before conducting an independent samples t-test?

Answer 16

Check the suitability of the data for each group (how normal they are)

Split the file

Question 17

After splitting a file to assess the normality of eacih group, remember to….

Answer 17

Merge them again!

Split file –> Analyse all cases

Question 18

How do we decide whether to use the equal variances assumed or not assumed value?

Answer 18

Levene’s test for the quality of variances

Is the variability the same?

Question 19

If the p-value for Levene’s test is significant, which row do you interpret?

Answer 19

The one where equal variance is NOT assumed

(the variability is statistically significantly different)

Question 20

What test would you use to see if the mean of a group in one condition is equal to the mean of the same (or paired) group in another condition?

Answer 20

Paired samples t-test

Question 21

What assumptions are needed for the paired samples t-test?

Answer 21

▪️The paired observations are randomly and independently drawn (only occur once)
▪️The paired differences variable is symmetrical and continuous
▪️There are no outliers in the difference

Question 22

What must you do before conducting a paired samples t-test?

Answer 22

Check how symmetrical the difference between the two are.

For this, you have to compute the variable (e.g. weight1-weight2)

Question 23

For what type of t-test do you need to check the variability (equality) of the variance?

Answer 23

Independent samples t-test (only)

Question 24

If the 95% CI of the difference includes 0, what can you conclude about the difference?

Answer 24

It is not statistically significant

Null hyoothes: difference = 0

Question 25

If the 95% CI of the difference does not include 0, what can you conclude about the difference?

Answer 25

The difference is statistically significant

Alternative hypothesis: difference does not equal 0