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 5479.167a 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 Differenceb
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 Differencea
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 Differenceb
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 Differenceb
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.