The words ‘independent’ and ‘dependent’ variables are terms in statistics class.Let me break down the meaning behind the terms. Let’s say you want to predict what makes a  bus come on time (1=on-time, 0=not on-time). So for several days you note whether or not the bus came on-time. Then you need to know under what conditions does the bus come on-time? So you do your research and discover that (1) the weather, (2) traffic, and (3) time of day determine if the bus will be on-time. Your independent variables are weather, traffic, and time of day. Why? Because we are not studying what makes them tick. According to statistical theory, independent variables are not influenced by any other factors in the model. They stand alone. So when you look at a homework problem and it mentions variables to consider try to classify each as either the dependent or independent variable. For a basic statistics course, only one of those variables will be dependent on the others. Suppose a homework problem focused on predicting high blood pressure due to obesity, stress, and weight. The high blood pressure is “dependent” upon whether or not someone has obesity, stress, and weight.  Now there are factors that cause obesity. One could argue that stress causes obesity. Stress can even make a person gain weight.You can easily determine the interaction of your independent variables to see if it is significant to the model.

But the key to recognizing the dependent variable is what is under study. Once you detect the outcome of interest it is easier to construct your statistical model.

I hope you enjoyed this blog, there are more to follow-Amy