Interpretation of correlation coefficient between two binary variables I have a dataset with binary variables for mitigation measures (0= a measure is not implemented, 1 = a measure is not implemented).
I now want to know how often a certain measure is put in place together with another measure. For this I used a  using the Pearson coeefficient.
How do I interpret the coefficients? For example the 0.18 interaction between expensive_contents and electricals_above? because the two do not show up together 18% of the time in the data, but around 9% of the time.

For binary data, the correlation coefficient is:
$$r = \frac{p_{11}-p_{1 \bullet} p_{\bullet 1}}{\sqrt{p_{1 \bullet} p_{\bullet 1} (1-p_{1 \bullet})(1-p_{\bullet 1})}},$$
where $p_{1 \bullet}$ and $p_{\bullet 1}$ are the proportions of occurrences for each individual variable and $p_{11}$ is the proportion of mutual occurrence in both variables taken together (the latter is your 18% in this case).  As you can see from the formula, it is not generally the case that $r=p_{11}$.  The formula also takes account of the proportion of occurrences in each of the individual samples.
