Week 7

Question 1

What is degrees of freedom?

Answer 1

The number of independent values or observations that can vary freely.

Question 2

Why is degrees of freedom calculated as n-1?

Answer 2

Because calculating the mean uses up information, constraining the dataset.

Question 3

What is the formula for degrees of freedom when calculating variance?

Answer 3

DF = n - 1.

Question 4

In a mixed ANOVA, how is the degrees of freedom for interaction calculated?

Answer 4

df for iv1 × df for iv2.

Question 5

What represents the error degrees of freedom in within-subjects ANOVA?

Answer 5

Number of participants per condition - 1 x number of conditions - 1.

Question 6

What is the formula for between-subjects error degrees of freedom?

Answer 6

Total participants - 1 - number of groups - 1.

Question 7

What does the error degrees of freedom represent?

Answer 7

Variation in the dependent variable that cannot be attributed to the independent variables.

Question 8

Was there a significant main effect of drink type on stats exam scores?

Answer 8

Yes, F(2, 10) = 17.38, p=.001.

Question 9

Was there a significant main effect of sleep on stats exam scores?

Answer 9

No, F(1, 5) = 3.16, p = .136.

Question 10

What does a significant Drink x Sleep interaction indicate?

Answer 10

The influence of drink on stats scores depends on the sleep condition.

Question 11

What are main effects in the context of ANOVA?

Answer 11

The influence of one independent variable irrespective of the others.

Question 12

What are interactions in the context of ANOVA?

Answer 12

How the effect of one variable depends upon another.

Question 13

What is the purpose of post-hoc tests?

Answer 13

To understand main effects if the independent variable has more than 2 levels.

Question 14

In a mixed ANOVA, what does one independent variable represent?

Answer 14

Manipulated between participants (e.g., food).

Question 15

What does the other independent variable represent in a mixed ANOVA?

Answer 15

Manipulated within participants (e.g., time of day).

Question 16

How should data be entered into SPSS for a mixed design?

Answer 16

One column for the between-subjects IV and columns for every level of the within-subjects IV.

Question 17

What is the output of a two-way mixed ANOVA?

Answer 17

Main effect of IV1, main effect of IV2, IV1 x IV2 interaction.

Question 18

What needs to be checked before interpreting the within-subjects effects table?

Answer 18

Mauchly’s test of sphericity.

Question 19

What does the Tests of Between-Subjects Effects table show?

Answer 19

The main effect of the between-subjects IV.

Question 20

What is the basic structure for reporting ANOVA results?

Answer 20

• Descriptive Statistics * Results of ANOVA * Interaction plot.

Question 21

What descriptive statistics should be included when reporting ANOVA?

Answer 21

Mean scores and standard deviations across all conditions.

Question 22

What type of mixed ANOVA was conducted in the example?

Answer 22

A 2 (time of day) x 3 (food type) mixed ANOVA.

Question 23

What significant result was found regarding food type in the mixed ANOVA?

Answer 23

Significant main effect of food type, F(2,15) = 3.36, p<.001.

Question 24

What does a significant interaction in ANOVA indicate?

Answer 24

The effect of one independent variable differs across levels of another independent variable.

Question 25

What are the two post-hoc tests mentioned for the mixed ANOVA?

Answer 25

* Bonferroni for within-subjects IV * Tukey for between-subjects IV.

Question 26

Fill in the blank: Degrees of freedom refer to the number of _______.

Answer 26

independent values or observations that can vary freely.

Question 27

True or False: There was no difference between the two sleep conditions.

Answer 27

True.

Question 28

What type of ANOVA was conducted in the study?

Answer 28

A 2 (time of day: morning (AM) or afternoon (PM)) x 3 (food; chocolate, apple, no food) mixed ANOVA. ## Footnote The first factor was manipulated within subjects and the latter between subjects.

Question 29

What was the significant main effect found regarding food type?

Answer 29

F(2,15) = 3.36, p < .001. ## Footnote This indicates that the type of food had a significant impact on reaction times.

Question 30

Was there a significant main effect of time of day?

Answer 30

No, F(1,15) = 8.06, p = .09. ## Footnote This suggests that time of day did not significantly affect reaction times.

Question 31

What was the result of the interaction effect between food type and time of day?

Answer 31

F(2,15) = 8.06, p < .01. ## Footnote This indicates a significant interaction between the type of food and time of day.

Question 32

Which food condition had significantly faster reaction times compared to the no food condition?

Answer 32

Chocolate and apple conditions. ## Footnote Both conditions had p < .001 compared to the no food condition.

Question 33

What were the reaction time results between chocolate and apple conditions?

Answer 33

No significant differences, p = .99. ## Footnote This indicates that the reaction times were similar in both conditions.

Question 34

What test was used to examine differences between food conditions?

Answer 34

Tukey's post-hoc test. ## Footnote This test is used to determine which specific group means are different.

Question 35

What assumptions are required for parametric tests?

Answer 35

* Normally distributed data * Homogeneity of variance * Ratio or interval data ## Footnote ANOVA is robust to violations of normality and homogeneity of variance if group sizes are equal.

Question 36

What is the 'rule of four' in relation to homogeneity of variance?

Answer 36

Take the largest standard deviation and divide by the smallest standard deviation; if the result is less than 4, the assumption is met. ## Footnote This method helps assess whether the assumption of homogeneity of variance holds.

Question 37

What is the non-parametric equivalent to a paired t-test?

Answer 37

Wilcoxon test. ## Footnote This test is used for within-subjects designs when assumptions for parametric tests are not met.

Question 38

What is the non-parametric equivalent to one-way independent ANOVA?

Answer 38

Kruskal-Wallis test. ## Footnote This test is used when comparing three or more independent groups.

Question 39

What is the non-parametric equivalent to one-way repeated-measures ANOVA?

Answer 39

Friedman's ANOVA. ## Footnote This test is used for within-subjects designs with more than two conditions.

Question 40

What is the limitation of non-parametric tests regarding interaction effects?

Answer 40

Interactions cannot be tested using a non-parametric test. ## Footnote Non-parametric tests require splitting the analysis into main effects.

Question 41

What should be reported if a significant main effect has more than two levels?

Answer 41

The results of the post-hoc tests. ## Footnote This provides insight into specific group differences.

Question 42

In a two-way mixed ANOVA, how should analysis be approached?

Answer 42

It needs to be split into individual factors. ## Footnote Different tests apply based on whether the IV is between-subjects or within-subjects.

Question 43

What tests are used for post-hoc analysis in within-subjects designs?

Answer 43

* Bonferroni (for the within-subjects IV) * Tukey (for the between-subjects IV) ## Footnote These tests help identify specific differences between group means.

Question 44

What do you need to check for sphericity in repeated measures ANOVA?

Answer 44

Yes, for the main effect of the within-subjects IV and the interaction. ## Footnote Sphericity is an assumption that must be checked to ensure valid results.