Results

Smart Alex Task 7.2

Gender identity is a categorical variable with two categories, therefore, we need to quantify this relationship using a point-biserial correlation. I have asked for the bootstrapped confidence intervals as they are robust. The figure below shows that there was no significant relationship between gender identity and arousal because the p-value is larger than 0.05 and the bootstrapped confidence intervals cross zero, π‘Ÿpb= –0.20, 95% BCa CI [–0.461, 0.137], p = 0.266.

Pearson's Correlations
Variable Β  gender_identity arousal
1. gender_identity n β€”
Pearson's r β€”
p-value β€” Β 
Lower 95% CI β€”
Upper 95% CI β€”
2. arousal n 40 β€”
Pearson's r -0.196 β€”
p-value 0.226 β€”
Lower 95% CI -0.461 β€”
Upper 95% CI 0.137 β€”
Note. Β Confidence intervals based on 1000 bootstrap replicates.

Smart Alex Task 7.3

There was a significant relationship between the film watched and arousal, π‘Ÿpb= –0.87, 95% BCa CI [–0.91, –0.81], p < 0.001. Looking in the data at how the groups were coded, you should see that The Notebook had a code of 1, and the documentary about notebooks had a code of 2, therefore the negative coefficient reflects the fact that as film goes up (changes from 1 to 2) arousal goes down. Put another way, as the film changes from The Notebook to a documentary about notebooks, arousal decreases. So The Notebook gave rise to the greater arousal levels.

Pearson's Correlations
Variable Β  film arousal
1. film n β€”
Pearson's r β€”
p-value β€” Β 
Lower 95% CI β€”
Upper 95% CI β€”
2. arousal n 40 β€”
Pearson's r -0.865 β€”
p-value <Β .001 β€”
Lower 95% CI -0.918 β€”
Upper 95% CI -0.798 β€”
Note. Β Confidence intervals based on 1000 bootstrap replicates.