Translating a regression line into a description in everyday terms
It’s natural to display a linear regression as a graph modeling the response variable as a function of the explanatory variables. In the Regression Modelling Little_App_Regression Little App, that function is shown as a line laid on top of the data.
Graphics are important, but it’s also a good practice to summarize the relationship using words and numbers.
This lesson introduces the conventions for such a summary. Some of them may already be familiar to you.
The relationship shown in the Little_App_Regression Little App is (by default) a straight line. In the Apps Control (the icon that is 3 parallel lines) allows you to change to other degree polynomials. (If there is a covariate, there will be multiple lines, one for each level of the covariate.) There are two important ways you can describe lines:
Find an explanatory variable that produces a regression line that slopes up. What is it? . . .
Find another explanatory variable where the regression line slopes down. What is it? . . .
For each of those two variables, find the numerical value of the slope of the line. Then summarize the relationship in this way:
As _______ (the explanatory variable) increases by ____, the response variable _____ will go up_or_down by _____.
In filling in the two blanks following “by”, make sure to give the units of the variables. You can find the units by looking at the codebook.
Version 0.3, 2020-08-14