First, we decided to split into two communality factors: The one we decided a priori (without perceived quality and attractiveness), and the one we decided upon a posteriori (including perceived quality and attractiveness). We decided on the second analysis, as a factor analysis on all items of the house could show that all the measurements could be narrowed down to one dependent variable 'communality_total', as suggested in one pilot study (IJzerman, 2013). Furthermore, we conducted a reliability analysis to determine if the used variables are reliable. Our analysis consists of multiple steps: - We did both a MANOVA and ANOVA to compare groups on both the separated communality items (attractiveness and quality separated) and the communality_total scores. - We also utilized an ANOVA to compare groups on need for affiliation. - To discover if the proposed mediating effect between the relationship between temperature and the evaluation of the house via Need for Affiliation was present, we leveraged a bootstrap procedure using Preacher and Hayes' (2008) INDIRECT macro, with 1000 resamples. - Finally, using the PROCESS macro by Hayes (2013), we explored whether daily temperature played a moderating role in our proposed effects.