Author: Dejan Sarka

SQL Server Database and BI Trainer, Consultant and Developer

High-Performance Statistical Queries: Dependencies Between Continuous and Discrete Variables

In my previous articles, I explained how you can check for associations between two continuous and two discrete variables. This time, we’ll check for linear dependencies between continuous and discrete variables. You can do this by measuring the variance between the means of the continuous variable and different groups of the discrete variable. The null hypothesis here is that all variances between the means are a result of the variance within each group.

High Performance Statistical Queries: Linear Dependencies Between Continuous Variables

In my previous articles, I dealt with analyses of only a single variable. Now it is time to check whether two variables of interest are independent or somehow related. For example, a person’s height positively correlates with shoe size. Taller people have larger shoe sizes, and shorter people have smaller shoe sizes. You can find this and many more examples of positive associations at: A negative association is also possible.