If the residuals are normally distributed, then in the normal Q-Q chart in Figure 16-6, the points

should lie close to the dotted diagonal line, and shouldn’t display any overall curved shape. Our

opinion is that the points follow the dotted line pretty well, so we’re not concerned about lack of

normality in the residuals.

Making your way through the regression table

When doing regression, it is common to focus on the table of regression coefficients. It’s likely

where you look first when interpreting your results, and where you concentrate most of your

attention. When you run a straight-line regression, statistical programs typically produce a table

of regression coefficients that looks much like the one in Figure 16-4 under the heading

Coefficients.

For straight-line regression, the coefficients table has two rows that correspond with the two

parameters of the straight line:

The intercept row: This row is labeled (Intercept) in Figure 16-4, but can be labeled Intercept or

Constant in other software.

The slope row: This row is usually labeled with the name of the independent variable in your

data, so in Figure 16-4, it is named Wgt. It may be labeled Slope in some programs.

The table has several different columns, depending on the software. In Figure 16-4, the columns are

Estimate, Std. Error, t value, and Pr (>|t|). How to interpret the results from these columns is

discussed in the next section.

The values of the coefficients (the intercept and the slope)

The first column of the table of regression coefficients usually shows the values of the slope

and intercept of the fitted straight line (labeled Estimate in Figure 16-4). Other column headings

include Coefficient or the single letter B or C (in uppercase or lowercase), depending on the

software.

Looking at the rows in Figure 16-4, the intercept (labeled (Intercept)) is the predicted value of Y when

X is equal to 0, and is expressed in the same units of measurement as the Y variable. The slope

(labeled Wgt) is the amount the predicted value of Y changes when X increases by exactly one unit of

measurement, and is expressed in units equal to the units of Y divided by the units of X.

In the example shown in Figure 16-4, the estimated value of the intercept is 76.8602 mmHg, and the

estimated value of the slope is 0.4871 mmHg/kg.

The intercept value of 76.9 mmHg means that a person who weighs 0 kg is predicted to have a SBP

of about 77 mmHg. But nobody weighs 0 kg! The intercept in this example (and in many straight-

line relationships in biology) has no physiological meaning at all, because 0 kg is completely

outside the range of possible human weights.