1. Learn
    2. /
  2. Courses
    3. /
  3. Data Analysis and Statistical Inference

Exercise

Breaking it down

In this exercise, you should first make the assignment described in the instructions below. After that, read the rest of this description.

First, the formula used to describe the model is shown at the top. After the formula you find the five-number summary of the residuals. The “Coefficients” table shown next is key; its first column displays the linear model’s y-intercept and the coefficient of homeruns. With this table, we can write down the least squares regression line for the linear model:

$$\hat{y} = 415.2389 + 1.8345~\mathrm{homeruns}$$

One last piece of information we will discuss from the summary output is the Multiple R-squared, or more simply, \(R^2\). The \(R^2\) value represents the proportion of variability in the response variable that is explained by the explanatory variable. For this model, 62.7% of the variability in runs is explained by homeruns.

Instructions

100 XP

Fit a new model that uses homeruns to predict runs. Using the estimates from the R output, write the equation of the regression line.