In: Math
Please note that for all problems in this course, the standard cut-off (alpha) for a test of significance will be .05, and you always report the exact power unless SPSS output states p=.000 (you’d report p<.001). Also, remember that we divide the p value in half when reporting one-tailed tests with 1 – 2 groups.
Problem Set 2: (8 pts) Research Scenario: Does distraction and/or amount of details affect the ability of people to make good decisions? In this fictitious scenario, researchers used a within-subjects design. Participants (N=15) were given four different scenarios based on amount of details (4 or 14) and distraction level (no distraction or distraction), and were asked to make an objective decision at the end of each scenario. Objective decision was the dependent variable and was quantified numerically using an interval scale of measurement. Each participant provided four objective decisions – one for each condition. Assume the data is parametric. Select and conduct the most appropriate statistical test to determine whether distraction and/or amount of details affect people’s ability to make good decisions. Hint: since this is within subjects, each level for each factor will have its own column of data, so you will have 4 columns of 15 rows of data in your SPSS data view. You will analyze two factors (“Distraction” and “Details”) and each factor has 2 levels. Please label your columns “NoDistract4”, “NoDistract14”, “Distract4”, and “Distract14”.
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Hypothesis for Distraction
Ho: The no distractive and distractive are from the population with the same mean
H1: The no distractive and distractive are from the population with different means.
Hypothesis for Details:
Ho: The 4 details and 14 details are from the population with the same mean
H1: The 4 details and 14 details are from the population with different means
Tests of Between-Subjects Effects | |||||
Dependent Variable:Y | |||||
Source | Type III Sum of Squares | df | Mean Square | F | Sig. |
Corrected Model | 13.901a | 2 | 6.951 | 2.053 | 0.138 |
Intercept | 719.681 | 1 | 719.681 | 212.572 | p<0.001 |
Distraction | 4.931 | 1 | 4.931 | 1.456 | 0.232 |
Details | 8.971 | 1 | 8.971 | 2.650 | 0.109 |
Error | 192.978 | 57 | 3.386 | ||
Total | 926.560 | 60 | |||
Corrected Total | 206.879 | 59 |
Distraction:
The p-value for the factor Distraction is 0.232 and more than 0.05 significance level. Hence, we fail to reject the null hypothesis and conclude that the factor Distraction does not have a significant effect on the people’s ability to make good decisions at the 0.05 significance level.
Details:
The p-value for the factor Detail is 0.109 and more than 0.05 significance level. Hence, we fail to reject the null hypothesis and conclude that the factor Detail does not have a significant effect on the people’s ability to make good decisions at the 0.05 significance level.
Type III Sum of Squares | Effect size | |
Distraction | 4.931 | 0.0053 |
Details | 8.971 | 0.0097 |
Total | 926.560 |
The post hoc analyses is not necessary because the main effects are insignificant.