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Illuminating Statistical Analysis Using Scenarios and Simulations by Jeffrey E. Kottemann

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42Using Binomials Too

Let's look at the results of a simple regression model with the scaled variable weight as img and the binomial variable sex as img. First, look at the (strange looking) scatterplot in Figure 42.1. All the male weights are bunched at img and all the female weights are bunched at img. The regression line will go through the average weight for males and the average weight for females because that is the least-squares fit.1

A graphical representation where weight is plotted on the y-axis on a scale of 0–250 and sex on the x-axis on a scale of 0–1.

Figure 42.1

How can we interpret the slope of this regression line? Rise/run, where the rise is the difference between the sample mean weight for males and the sample mean weight for females, and the run is 1. The slope, then, is simply the difference in the sample means. That is what img will be. And the -intercept, ...

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