What is the relationship between the attendance at a major league ball game and the total number of runs scored? Attendance figures (in thousands) and the runs scored for 10 randomly selected games are shown below. Attendance 45 14 39 59 40 52 54 14 26 58 Runs 7 2 6 14 7 10 14 6 9 13 Interpret r2r2 : There is a 69% chance that the regression line will be a good predictor for the runs scored based on the attendance of the game. Given any fixed attendance, 69% of all of those games will have the predicted number of runs scored. 69% of all games will have the average number of runs scored. There is a large variation in the runs scored in baseball games, but if you only look at games with a fixed attendance, this variation on average is reduced by 69%. The equation of the linear regression line is: ˆyy^ = + xx (Please show your answers to two decimal places) Use the model to predict the runs scored at a game that has an attendance of 39,000 people. Runs scored = (Please round your answer to the nearest whole number.) Interpret the slope of the regression line in the context of the question: As x goes up, y goes up. The slope has no practical meaning since the total number runs scored in a game must be positive. For every additional thousand people who attend a game, there tends to be an average increase of 0.19 runs scored. Interpret the y-intercept in the context of the question: The best prediction for a game with 0 attendance is that there will be 1 runs scored. The average runs scored is predicted to be 1. If the attendance of a baseball game is 0, then 1 runs will be scored. The y-intercept has no practical meaning for this study.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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What is the relationship between the attendance at a major league ball game and the total number of runs scored? Attendance figures (in thousands) and the runs scored for 10 randomly selected games are shown below.

Attendance	45	14	39	59	40	52	54	14	26	58
Runs	7	2	6	14	7	10	14	6	9	13

Interpret r2r2 :
- There is a 69% chance that the regression line will be a good predictor for the runs scored based on the attendance of the game.
- Given any fixed attendance, 69% of all of those games will have the predicted number of runs scored.
- 69% of all games will have the average number of runs scored.
- There is a large variation in the runs scored in baseball games, but if you only look at games with a fixed attendance, this variation on average is reduced by 69%.
The equation of the linear regression line is:
ˆyy^ = + xx (Please show your answers to two decimal places)
Use the model to predict the runs scored at a game that has an attendance of 39,000 people.
Runs scored = (Please round your answer to the nearest whole number.)
Interpret the slope of the regression line in the context of the question:
- As x goes up, y goes up.
- The slope has no practical meaning since the total number runs scored in a game must be positive.
- For every additional thousand people who attend a game, there tends to be an average increase of 0.19 runs scored.
Interpret the y-intercept in the context of the question:
- The best prediction for a game with 0 attendance is that there will be 1 runs scored.
- The average runs scored is predicted to be 1.
- If the attendance of a baseball game is 0, then 1 runs will be scored.
- The y-intercept has no practical meaning for this study.

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