Question

How does gender and occupational prestige affect credibility? Graduate students in a public health program are asked to rate the strength of a paper about the health risks of childhood obesity. In reality, all student raters are given the same paper, but the name and degree associated with the author are changed. The student raters are randomly assigned to one group from the following name ("John Lake", "Joan Lake") and degree (M.D., R.N., Ph.D.) combination. The raters score the paper from 1 to 5 on clarity, strength of argument, and thoroughness. The total scores (the sum of the three scores) are given in the table below. What can be concluded with an α of 0.05?

John Lake / M.D.	John Lake / R.N.	John Lake / Ph.D.	Joan Lake / M.D.	Joan Lake / R.N.	Joan Lake / Ph.D.
12 15 13 15 14	15 16 12 13 13	11 8 13 12 9	15 10 12 14 12	10 7 8 10 6	11 11 12 8 8

a) What is the appropriate test statistic?
---Select--- na one-way ANOVA within-subjects ANOVA two-way ANOVA

b) Compute the appropriate test statistic(s) to make a decision about H₀.
Name: p-value =  ; Decision:  ---Select--- Reject H0 Fail to reject H0
Degree: p-value =  ; Decision:  ---Select--- Reject H0 Fail to reject H0
Interaction: p-value =  ; Decision:  ---Select--- Reject H0 Fail to reject H0


c) Compute the corresponding effect size(s) and indicate magnitude(s).
Name: η² =  ;  ---Select--- na trivial effect small effect medium effect large effect
Degree: η² =  ;  ---Select--- na trivial effect small effect medium effect large effect
Interaction: η² =  ;  ---Select--- na trivial effect small effect medium effect large effect


d) Make an interpretation based on the results.

There is a name difference in the total scores.There is no name difference in the total scores.    

There is a degree difference in the total scores.There is no degree difference in the total scores.    

There is a name by degree interaction in the total scores.There is no name by degree interaction in the total scores.    

Answer 1

ANSWER

a)
two-way ANOVA is applied here as there are 2 factors here.
factor 1 is name. it has 2 levels namely John Lake and Joan Lake.
factor 2 is degree. it has 3 levels namely MD, RN, PhD.

b)

Ho1: main effect of name is no significant. V/s h1: main effect of name is significant. With p<5%, i reject ho and conclude that main effect of name is significant.

Ho1: main effect of degree is no significant. V/s h1: main effect of degree is significant. With p<5%, i reject ho and conclude that main effect of degree is significant.

Ho1: main effect of interaction is no significant. V/s h1: main effect of interaction is significant. With p<5%, i reject ho and conclude that main effect of interaction is significant.

Name: p-value = 0.000925481; Decision: ---Select--- Reject H0
Degree: p-value = 0.003651312; Decision: ---Select--- Reject H0
Interaction: p-value = 0.0086782; Decision: ---Select--- Reject H0

c)

η² = SS_between/SS_total

Name: η2 = =45.633/205.5 =   0.222058394 ; ---Select--- small effect
Degree: η2 = =45.8/205.5 =   0.222871046 ; ---Select--- small effect
Interaction: η2 = =35.2667/205.5 =   0.171614112 ; ---Select--- small effect

d)

Ho1: main effect of name is no significant. V/s h1: main effect of name is significant. With p<5%, i reject ho and conclude that main effect of name is significant.

Ho1: main effect of degree is no significant. V/s h1: main effect of degree is significant. With p<5%, i reject ho and conclude that main effect of degree is significant.

Ho1: main effect of interaction is no significant. V/s h1: main effect of interaction is significant. With p<5%, i reject ho and conclude that main effect of interaction is significant.

There is a name difference in the total scores.
There is a degree difference in the total scores.
There is a name by degree interaction in the total scores.

procedure:

output: