*4.1. Statistical Analyses*

The results section is organized as follows. First, we present descriptive statistics for the demographic and control variables. Second, we describe details on measures and materials used in a study, the measure of energy monitoring, the measures of an attitude towards environmental issues, and knowledge on the energy market.

Analyses were performed using statistical language R v. 3.4.3 (RCore Team, 2019) for logistic regression models and IBM SPSS Statistics v. 25 for the rest of the analyses performed. To construct measures of attitudes towards energy monitoring and pro-environmental issues, we reduced the number of the items into meaningful components by means of the Principle Components Analysis (PCA).

Then, we directly addressed stated hypotheses and explored whether the time of measurement (T0, T4, T5) and the experimental manipulation predicted phase changes (F1–F4). Next, we tested correlations between monitoring of energy consumption and attitude towards pro-environmental issues and a the level of education, and knowledge. All analyses were conducted in the frequentist approach with *α*-level set to 0.05.
