1. Predicting runs from hits a. Read in the baseball data set from Homework 4. b. Fit a linear regression model that predicts Runs based on the number of Hits. c. Print out a summary of your model d. What is the R-squared for your model?

Step-by-step explanation:

Hello!

You need to find the linear regression model that predicts Runs based on the number of Hits using the information of 6 Baseball Teams.

The dependent variable is:

Y: Number of runs made by a baseball team.

The explanatory variable is

X: Number of hits made by a baseball team.

The estimated regression model is

^Y= a + bX

Using the given data you have to estimate the intercept and the slope of the linear model.

a= -311.58

b= 0.74

^Y= -311.58 + 0.74X

The coefficient of determination for this regression model is R²=0.75

This means that 75% of the variability of the number of runs made by the teams can be explained by the number of hits, under the estimated model

^Y= -311.58 + 0.74X

I hope it helps!

i'm not really sure how to answer that

step-by-step explanation:

step-by-step explanation:

i'm not sure how to show the work for this

answer : c and d or 4(29 + 6)

4(29) + 4(6)