I’m working on a statistics discussion question and need support to help me learn.

When I think of linearity, it’s a straight line. Back when I was in school I used to love doing math problems in algebra. However, Corty (2016) states that a predictor variable is used to predict one state over another variable, and the prediction equation takes the straight line. There are three linear regressions. The first implementation is simple. The second linear data can be separated, and the third will help reduce overfitting. One of the studies they conducted was that medical researchers conducted a study to find out the relationship between drug dose and blood pressure in patients (Zach, 2020). This is useful for researchers to see how medications help a patient, such as whether the treatment benefits the patient. Another test can help determine if the community means it is significant; However, linearity is more effective at linking two different variables together and seeing the linear connection.