In: Statistics and Probability
A study by Staub, 1970, was concerned with the effects of instructions to young children and their subsequent attempts to help another child (apparently) in distress. Twenty-four first-grade students were randomly assigned to one of three groups. The first group was labeled as indirect responsibility (IR). Students in the IR group were informed that another child was alone in an adjoining room and had been warned not to climb up on a chair. The second group was labeled direct responsibility one (DR1). Students in the DR1 group were told the same story as in the IR condition, but was also told that they were left in charge and to take care of anything that happened. The students were given a simple task, and the researcher left the room. The students then heard a loud crash in the adjoining room followed by a minute of sobbing and crying. Students in the third group, direct responsibility two (DR2), had the same instructions as the DR1 group, but the sounds of distress also included calls for help. Ratings from 1 (no help) to 5 (went to the adjoining room) were given to each student by an observer sitting behind a one-way mirror. The ratings are given below. Perform a one-way ANOVA in SPSS with α = .05 and answer the following questions:
IR |
DR1 |
DR2 |
3 |
5 |
4 |
4 |
4 |
4 |
2 |
5 |
3 |
1 |
4 |
3 |
1 |
5 |
4 |
2 |
5 |
2 |
1 |
4 |
5 |
1 |
3 |
3 |
PART A: Perform ANOVA analysis using SPSS and present the results in a tabular format (do not copy and paste SPSS’s output).
PART B: Calculate the effect size (w2) and interpret (in words) its meaning.
PART A: Perform ANOVA analysis using SPSS and present the results in a tabular format (do not copy and paste SPSS’s output).
Group |
F |
Significance |
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IR |
DR1 |
DR2 |
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Mean |
1.875 |
4.375 |
3.500 |
14.420 |
P< 0.001 |
Std. Deviation |
1.126 |
0.744 |
0.926 |
Calculated F=14.42, P< 0.001 . The null hypothesis is rejected. There is significant difference between the three group means.
PART B: Calculate the effect size (w2) and interpret (in words) its meaning.
effect size = 25.75/44.5 = 0.579
since calculated effect size 0.579 is > 0.36, the effect size is strong.
Spss output:
Descriptive Statistics |
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Dependent Variable: data |
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Group |
Mean |
Std. Deviation |
N |
IR |
1.8750 |
1.12599 |
8 |
DR1 |
4.3750 |
.74402 |
8 |
DR2 |
3.5000 |
.92582 |
8 |
Total |
3.2500 |
1.39096 |
24 |
Tests of Between-Subjects Effects |
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Dependent Variable: data |
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Source |
Type III Sum of Squares |
df |
Mean Square |
F |
Sig. |
Partial Eta Squared |
Corrected Model |
25.750a |
2 |
12.875 |
14.420 |
.000 |
.579 |
Intercept |
253.500 |
1 |
253.500 |
283.920 |
.000 |
.931 |
Group |
25.750 |
2 |
12.875 |
14.420 |
.000 |
.579 |
Error |
18.750 |
21 |
.893 |
|||
Total |
298.000 |
24 |
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Corrected Total |
44.500 |
23 |
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a. R Squared = .579 (Adjusted R Squared = .539) |