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 12 randomly selected games are shown below. Attendance Runs 25 34 42 23 29 30 45 29 8 3 3 3 11 20 42 51 22 29 7 7 9 3 8 a. Find the correlation coefficient: b. The null and alternative hypotheses for correlation are: 0 He: ( H₁:20 The p-value is: Round to 2 decimal places. (Round to four decimal places) c. Use a level of significance of a 0.05 to state the conclusion of the hypothesis test in the context of the study. There is statistically significant evidence to conclude that there is a correlation between the attendance of baseball games and the runs scored. Thus, the regression line is useful. There is statistically significant evidence to conclude that a game with higher attendance will have fewer runs scored than a game with lower attendance. There is statistically significant evidence to conclude that a game with a higher attendance will have more runs scored than a game with lower attendance. O There is statistically insignificant evidence to conclude that there is a correlation between the attendance of baseball games and the runs scored. Thus, the use of the regression line is not appropriate. (Round to two decimal places) (Round to two decimal places) d. ²= e. Interpret ²: Ⓒ 49% of all games will have the average number of runs scored. O Given any fixed attendance, 49% of all of those games will have the predicted 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 49%. f. The equation of the linear regression line is: O There is a 49% chance that the regression line will be a good predictor for the runs scored based on the attendance of the game. z (Please show your answers to two decimal places) g. 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.)

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Question

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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 12 randomly selected games are shown
below.
Attendance
Runs
25 34 42
2
9
8
0
#0
23 29 30
3 3
3
a. Find the correlation coefficient: r =
b. The null and alternative hypotheses for correlation are:
Ho:
H₁:2
The p-value is:
45
11
20 42
7
51 22 29
7 9 3 8
Round to 2 decimal places.
d. ² =
e. Interpret ²:
(Round to four decimal places)
c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context
of the study.
O There is statistically significant evidence to conclude that there is a correlation between the
attendance of baseball games and the runs scored. Thus, the regression line is useful.
O There is statistically significant evidence to conclude that a game with higher attendance will
have fewer runs scored than a game with lower attendance.
O There is statistically significant evidence to conclude that a game with a higher attendance
will have more runs scored than a game with lower attendance.
O There is statistically insignificant evidence to conclude that there is a correlation between the
attendance of baseball games and the runs scored. Thus, the use of the regression line is not
appropriate.
(Round to two decimal places) (Round to two decimal places)
f. The equation of the linear regression line is:
O 49% of all games will have the average number of runs scored.
O Given any fixed attendance, 49% of all of those games will have the predicted 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 49%.
There is a 49% chance that the regression line will be a good predictor for the runs score
based on the attendance of the game.
z (Please show your answers to two decimal places)
g. 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.)
Transcribed Image Text: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 12 randomly selected games are shown below. Attendance Runs 25 34 42 2 9 8 0 #0 23 29 30 3 3 3 a. Find the correlation coefficient: r = b. The null and alternative hypotheses for correlation are: Ho: H₁:2 The p-value is: 45 11 20 42 7 51 22 29 7 9 3 8 Round to 2 decimal places. d. ² = e. Interpret ²: (Round to four decimal places) c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context of the study. O There is statistically significant evidence to conclude that there is a correlation between the attendance of baseball games and the runs scored. Thus, the regression line is useful. O There is statistically significant evidence to conclude that a game with higher attendance will have fewer runs scored than a game with lower attendance. O There is statistically significant evidence to conclude that a game with a higher attendance will have more runs scored than a game with lower attendance. O There is statistically insignificant evidence to conclude that there is a correlation between the attendance of baseball games and the runs scored. Thus, the use of the regression line is not appropriate. (Round to two decimal places) (Round to two decimal places) f. The equation of the linear regression line is: O 49% of all games will have the average number of runs scored. O Given any fixed attendance, 49% of all of those games will have the predicted 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 49%. There is a 49% chance that the regression line will be a good predictor for the runs score based on the attendance of the game. z (Please show your answers to two decimal places) g. 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.)
h. Interpret the slope of the regression line in the context of the question:
O For every additional thousand people who attend a game, there tends to be an average
increase of 0.21 runs scored.
The slope has no practical meaning since the total number runs scored in a game must be
positive.
As x goes up, y goes up.
i. 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.
O If the attendance of a baseball game is 0, then -1 runs will be scored.
O The average runs scored is predicted to be -1.
O The y-intercept has no practical meaning for this study.
Transcribed Image Text:h. Interpret the slope of the regression line in the context of the question: O For every additional thousand people who attend a game, there tends to be an average increase of 0.21 runs scored. The slope has no practical meaning since the total number runs scored in a game must be positive. As x goes up, y goes up. i. 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. O If the attendance of a baseball game is 0, then -1 runs will be scored. O The average runs scored is predicted to be -1. O The y-intercept has no practical meaning for this study.
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