Exploring associations between continuous variables

For a single continuous variable, I introduced a couple of measures for the spread. One of the basic measures for the spread is the variance. If you have two continuous variables, each one has its own variance. However, you can ask yourself whether these two variables vary together. For example, if a value for the first variable of some case is quite high, well above the mean of the first variable, the value of the second variable of the same case could also be above its own mean. This would be a positive association. If the value of the second variable would be lower when the value for the first one is higher, then you would have a negative association. If there is no connection between the positive and negative deviations from the mean for both variables, then you can accept the null hypothesis—there is no association between these two variables. The formula for the covariance, which is the first measure for the association I am introducing...