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 8 randomly selected games are shown below. Attendance 14 44 21 13 22 43 38 16 Runs 5 13 9 8 8 13 9 6 Find the correlation coefficient: r=r= Round to 2 decimal places. The null and alternative hypotheses for correlation are: H0:H0: ? ρ μ r == 0 H1:H1: ? μ ρ r ≠≠ 0 The p-value is: (Round to four decimal places) Use a level of significance of α=0.05α=0.05 to state the conclusion of the hypothesis test in the context of the study. 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. 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 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. r2r2 = (Round to two decimal places) (Round to two decimal places) Interpret r2r2 : Given any fixed attendance, 78% 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 78%. There is a 78% chance that the regression line will be a good predictor for the runs scored based on the attendance of the game. 78% of all games will have the average number of runs scored. 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 21,000 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: For every additional thousand people who attend a game, there tends to be an average increase of 0.19 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. Interpret the y-intercept in the context of the question: The best prediction for a game with 0 attendance is that there will be 4 runs scored. If the attendance of a baseball game is 0, then 4 runs will be scored. The average runs scored is predicted to be 4. The y-intercept has no practical meaning for this study.

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 8 randomly selected games are shown below. Attendance 14 44 21 13 22 43 38 16 Runs 5 13 9 8 8 13 9 6 Find the correlation coefficient: r=r= Round to 2 decimal places. The null and alternative hypotheses for correlation are: H0:H0: ? ρ μ r == 0 H1:H1: ? μ ρ r ≠≠ 0 The p-value is: (Round to four decimal places) Use a level of significance of α=0.05α=0.05 to state the conclusion of the hypothesis test in the context of the study. 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. 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 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. r2r2 = (Round to two decimal places) (Round to two decimal places) Interpret r2r2 : Given any fixed attendance, 78% 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 78%. There is a 78% chance that the regression line will be a good predictor for the runs scored based on the attendance of the game. 78% of all games will have the average number of runs scored. 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 21,000 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: For every additional thousand people who attend a game, there tends to be an average increase of 0.19 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. Interpret the y-intercept in the context of the question: The best prediction for a game with 0 attendance is that there will be 4 runs scored. If the attendance of a baseball game is 0, then 4 runs will be scored. The average runs scored is predicted to be 4. 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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Attendance	14	44	21	13	22	43	38	16
Runs	5	13	9	8	8	13	9	6

Find the correlation coefficient: r=r= Round to 2 decimal places.

The null and alternative hypotheses for correlation are:
H0:H0: ? ρ μ r  == 0
H1:H1: ? μ ρ r   ≠≠ 0
The p-value is:    (Round to four decimal places)

Use a level of significance of α=0.05α=0.05 to state the conclusion of the hypothesis test in the context of the study.

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.
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 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.

r2r2 = (Round to two decimal places) (Round to two decimal places)

Interpret r2r2 :

Given any fixed attendance, 78% 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 78%.
There is a 78% chance that the regression line will be a good predictor for the runs scored based on the attendance of the game.
78% of all games will have the average number of runs scored.

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 21,000 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:

For every additional thousand people who attend a game, there tends to be an average increase of 0.19 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.

Interpret the y-intercept in the context of the question:

The best prediction for a game with 0 attendance is that there will be 4 runs scored.
If the attendance of a baseball game is 0, then 4 runs will be scored.
The average runs scored is predicted to be 4.
The y-intercept has no practical meaning for this study.

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