You will be completing this to mastery which means you will continue to turn it in until you have received a 100%. I will be getting feedback to you within 4 days of you turning it in. You then turn it back to me within 4 days if revisions are needed. This process will be repeated until you receive 100%. If you do not receive 100% or you do not turn it in, then you will be deducted 10 pts off your final total mastery points. Thus this exercise is not worth points, but if you do not do it then you will be deducted points.
See assignment here: Factorial designs.docx
Writing-up research results 1: Factorial ANOVA
Rules: You will be completing this assignment to mastery which means you will continue to turn it in until you have received a 100%. I will be getting feedback to you within 4 days of you turning it in. You then turn it back to me within 4 days if revisions are needed. This process will be repeated until you receive 100%. If you do not receive 100% or you do not turn it in, then you will be deducted 10 pts of your final total mastery points. Thus this exercise is not worth points, but if you do not do it then you will be deducted points.
Initial due date: Feb 27 by 11:59 pm
Field (2013) discuss a data set called “goggles.” In this study:
An anthropologist was interested in the effects of alcohol on mate selection in night clubs. Her rationale was that after alcohol had been consumed, subjective perceptions of physical attractiveness would become more inaccurate. She was also interested in whether this effect was different for men and women. She picked 48 students: 24 males and 24 females. She then took groups of eight participants to a nightclub and gave them no alcohol (participants received placebo drinks of alcohol-free lager), 2 pints of strong lager, or 4 pints of strong lager. At the end of the evening she took a photograph of the person that the participant was chatting up. She then got a pool of independent judges to assess the attractiveness of the person in each photograph (out of 100; Field, 2013, p. 510).
Below is the analysis:
Between-Subjects Factors | |||
Value Label | N | ||
Alcohol Consumption | 1 | None | 16 |
2 | 2 Pints | 16 | |
3 | 4 Pints | 16 | |
Gender | 0 | Male | 24 |
1 | Female | 24 |
Descriptive Statistics | ||||
Dependent Variable: Attractiveness of Date | ||||
Alcohol Consumption | Gender | Mean | Std. Deviation | N |
None | Male | 66.88 | 10.329 | 8 |
Female | 60.62 | 4.955 | 8 | |
Total | 63.75 | 8.466 | 16 | |
2 Pints | Male | 66.87 | 12.518 | 8 |
Female | 62.50 | 6.547 | 8 | |
Total | 64.69 | 9.911 | 16 | |
4 Pints | Male | 35.63 | 10.836 | 8 |
Female | 57.50 | 7.071 | 8 | |
Total | 46.56 | 14.343 | 16 | |
Total | Male | 56.46 | 18.503 | 24 |
Female | 60.21 | 6.338 | 24 | |
Total | 58.33 | 13.812 | 48 |
Tests of Between-Subjects Effects | |||||
Dependent Variable: Attractiveness of Date | |||||
Source | Type III Sum of Squares | df | Mean Square | F | Sig. |
Corrected Model | 5479.167^{a} | 5 | 1095.833 | 13.197 | .000 |
Intercept | 163333.333 | 1 | 163333.333 | 1967.025 | .000 |
Alcohol | 3332.292 | 2 | 1666.146 | 20.065 | .000 |
Gender | 168.750 | 1 | 168.750 | 2.032 | .161 |
Alcohol * Gender | 1978.125 | 2 | 989.063 | 11.911 | .000 |
Error | 3487.500 | 42 | 83.036 | ||
Total | 172300.000 | 48 | |||
Corrected Total | 8966.667 | 47 | |||
a. R Squared = .611 (Adjusted R Squared = .565) |
Pairwise Comparisons | ||||||
Dependent Variable: Attractiveness of Date | ||||||
(I) Alcohol Consumption | (J) Alcohol Consumption | Mean Difference (I-J) | Std. Error | Sig.^{b} | 95% Confidence Interval for Difference^{b} | |
Lower Bound | Upper Bound | |||||
None | 2 Pints | -.938 | 3.222 | .772 | -7.439 | 5.564 |
4 Pints | 17.188^{*} | 3.222 | .000 | 10.686 | 23.689 | |
2 Pints | None | .938 | 3.222 | .772 | -5.564 | 7.439 |
4 Pints | 18.125^{*} | 3.222 | .000 | 11.623 | 24.627 | |
4 Pints | None | -17.188^{*} | 3.222 | .000 | -23.689 | -10.686 |
2 Pints | -18.125^{*} | 3.222 | .000 | -24.627 | -11.623 | |
Based on estimated marginal means | ||||||
*. The mean difference is significant at the .05 level. | ||||||
b. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments). |
Pairwise Comparisons | ||||||
Dependent Variable: Attractiveness of Date | ||||||
(I) Gender | (J) Gender | Mean Difference (I-J) | Std. Error | Sig.^{a} | 95% Confidence Interval for Difference^{a} | |
Lower Bound | Upper Bound | |||||
Male | Female | -3.750 | 2.631 | .161 | -9.059 | 1.559 |
Female | Male | 3.750 | 2.631 | .161 | -1.559 | 9.059 |
Based on estimated marginal means | ||||||
a. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments). |
The next output is from the following syntax:
GLM Attractiveness BY Gender Alcohol
/EMMEANS = TABLES(Gender*Alcohol) COMPARE(Gender).
Pairwise Comparisons | |||||||
Dependent Variable: Attractiveness of Date | |||||||
Alcohol Consumption | (I) Gender | (J) Gender | Mean Difference (I-J) | Std. Error | Sig.^{b} | 95% Confidence Interval for Difference^{b} | |
Lower Bound | Upper Bound | ||||||
None | Male | Female | 6.250 | 4.556 | .177 | -2.945 | 15.445 |
Female | Male | -6.250 | 4.556 | .177 | -15.445 | 2.945 | |
2 Pints | Male | Female | 4.375 | 4.556 | .342 | -4.820 | 13.570 |
Female | Male | -4.375 | 4.556 | .342 | -13.570 | 4.820 | |
4 Pints | Male | Female | -21.875^{*} | 4.556 | .000 | -31.070 | -12.680 |
Female | Male | 21.875^{*} | 4.556 | .000 | 12.680 | 31.070 | |
Based on estimated marginal means | |||||||
*. The mean difference is significant at the .050 level. | |||||||
b. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments). |
The next output is from the following syntax:
GLM Attractiveness BY Gender Alcohol
/EMMEANS = TABLES(Gender*Alcohol) COMPARE(Alcohol).
Pairwise Comparisons | |||||||
Dependent Variable: Attractiveness of Date | |||||||
Gender | (I) Alcohol Consumption | (J) Alcohol Consumption | Mean Difference (I-J) | Std. Error | Sig.^{b} | 95% Confidence Interval for Difference^{b} | |
Lower Bound | Upper Bound | ||||||
Male | None | 2 Pints | -7.105E-15 | 4.556 | 1.000 | -9.195 | 9.195 |
4 Pints | 31.250^{*} | 4.556 | .000 | 22.055 | 40.445 | ||
2 Pints | None | 7.105E-15 | 4.556 | 1.000 | -9.195 | 9.195 | |
4 Pints | 31.250^{*} | 4.556 | .000 | 22.055 | 40.445 | ||
4 Pints | None | -31.250^{*} | 4.556 | .000 | -40.445 | -22.055 | |
2 Pints | -31.250^{*} | 4.556 | .000 | -40.445 | -22.055 | ||
Female | None | 2 Pints | -1.875 | 4.556 | .683 | -11.070 | 7.320 |
4 Pints | 3.125 | 4.556 | .497 | -6.070 | 12.320 | ||
2 Pints | None | 1.875 | 4.556 | .683 | -7.320 | 11.070 | |
4 Pints | 5.000 | 4.556 | .279 | -4.195 | 14.195 | ||
4 Pints | None | -3.125 | 4.556 | .497 | -12.320 | 6.070 | |
2 Pints | -5.000 | 4.556 | .279 | -14.195 | 4.195 | ||
Based on estimated marginal means | |||||||
*. The mean difference is significant at the .050 level. | |||||||
b. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments). |
Write-up in full paragraph form the results. In other words, using proper language and numbers write-up the results like you would in a research paper in the results section.