Jasp

Question 1

What is the first step you take when you open a data file in Jasp?

Answer 1

Label the values and check for missing values using frequency distribution

Question 2

What do you do when you are asked about the reliability of a set of questions?

Answer 2

Perform unidimensional reliability and check ‘Cronbach’s Alpha’ and item dropped. Report Alpha.

Question 3

What do you do when you are asked to calculate the correlation between two variables?

Answer 3

Go to correlation and check Pearson’s r for interval level of measurement. Report the correlation as well as p.

Question 4

What correlation test do you use for an ordinal level of measurement?

Answer 4

The Spearman’s rho test.

Question 5

What correlation test do you use for an interval level of measurement?

Answer 5

The Pearson’s r test.

Question 6

What do you check for when you see that data consists of ratings on a scale?

Answer 6

Check whether the scales have the same on 1 and 5 or if they are reversed.

Question 7

What do you do when you are asked to compare the means of two different groups?

Answer 7

Perform a t-test for independent groups. Chek ‘descriptives’ and ‘equal variances’.

Question 8

What do you do when you are asked to compare the means from the same group in repeated measurements?

Answer 8

Perform a t-test for dependent groups, a paired samples test

Question 9

How do you report on a t-test for independent samples?

Answer 9

Report t(df) = t, p=p. E.g.: (t(30)=1.3, p=0.05).

Question 10

What do you do if Levene’s test is significant?

Answer 10

Check ‘Welch’ and report those values

Question 11

What does t signify?

Answer 11

t tells you how many standard deviations the value is from the mean. The bigger t, the more you can reject H0.

Question 12

What do you do when you are asked if the variances in two or more groups are equal?

Answer 12

Go to ANOVA > Classical ANOVA.
Select dependent and independent variables in ‘Dependent variable’ and ‘Fixed factors’.
Check ‘estimates of effect size’, omega^2 and eta squared, ‘Homogeneity tests’

Question 13

What do you need to do extra when performing variance analysis for planned comparison?

Answer 13

Open ‘Contrasts’.
Select ‘custom’ instead of ‘none’
Enter values

Question 14

What do you need to do extra in a analysis of variance for post hoc comparison?

Answer 14

Open ‘Post Hoc Tests’ and move the factor there.
Check that ‘Type’ is standard
Check option ‘Effect size’
Check Tukey under ‘Correction’
Check Confidence intervals under ‘Display’

Question 15

How do you perform a two-way analysis of variance?

Answer 15

ANOVA > Classical ANOVA
under ‘Display’, check ‘Estimates of effect size’ and select eta + omega
Possible to also check ‘Descriptive statistics’
For ‘Sum of squares’ in ‘Model’, choose Type III.
Check ‘Homogeneity tests’

Question 16

What do you need to do extra when performing a two-way analysis of variance for post hoc comparison?

Answer 16

Open ‘Post hoc tests’ and move interaction to the right field.
Check if ‘Type’ is standard and if ‘Effect size’ is checked.
Under ‘Correction’, check Tukey.
Under ‘Display’, check confidence intervals

Question 17

How do you only use a selection of participants for a statistic?

Answer 17

Go to the same place where you change the labels and check the ‘v’ so that it becomes an ‘x’.

Question 18

Where do you use horizontal lines in an APA table?

Answer 18

To mark the top and bottom of the table, and to separate the headers from the body.

Question 19

How and where do you indicate the number of observations in an APA table?

Answer 19

Use (N=…) for the total number of observations and (n=…) for a subset.
Behind the title if there is no difference within the table, and below the headers if it is different per header.

Question 20

When do you leave out the 0 before the decimal point?

Answer 20

If the value is between 0 and 1 or between -1 and +1 and never could be outside that range

Question 21

How does data need to be entered in order to use X^2-test?

Answer 21

In the form of a summary of numbers of observations per category of the nominal variabel instead of one long column.