Ginger Grant gives a brief discussion of linear regression:

There are two types of indicators for linear correlation, positive and negative as shown on the following charts. The Y axis represents Grades, and the x axis is changed to show positive and negative correlation of the amount of X on grades. When X is the amount of study hours, there is a positive correlation and the line goes up. When X is changed to watching cat videos, there is a negative correlation. If you can’t draw a line around the points there is no correlation. If I were to create a graph where X indicated the quantity of the bags of Cheese Doodles consumed on grades, it would not be possible to draw a straight line, where the data points cluster around it. Since this is

Line-ar regression, if that line doesn’t exist there is no correlation. Knowing there is no correlation is also useful.

Simple linear regression is a powerful tool and gets you to “good enough” more frequently than you’d think.

Kevin Feasel

2016-04-08

Cloud, Data Science