Describing relationship patterns in words and numbers

Translating a regression line into a description in everyday terms

Helen Burn , Daniel Kaplan

Alternative document formats: Word & PDF


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:


  1. Open up the Little_App_Regression Little App. (See footnote1). Select Little Apps as the Source package,NHANES2 as the data set and systolic blood pressure as the response variable.

    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