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 15 55 23 18 48 26 29 27 21 14 18 11 Runs 7 12 7 1 10 3 6. 7 6 4 a. Find the correlation coefficient: r = 0.71 Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: Ho: pvV H1: pv + 0 o o The p-value is: 0.0097 o (Round to four decimal places) c. Use a level of significance of a of the study. 0.05 to state the conclusion of the hypothesis test in the context 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 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 there is a correlation between the attendance of baseball games and the runs scored. Thus, the regression line is useful. 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. d. 12 (Round to two decimal places) (Round to two decimal places) e. Interpret r2: O There is a 50% chance that the regression line will be a good predictor for the runs scored based on the attendance of the game. O Given any fixed attendance, 50% of all of those games will have the predicted number of runs scored. O 50% of all games will have the average number of runs scored. O 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 50%. f. The equation of the linear regression line is: y = x (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 29,000 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 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 0.16 runs scored. i. Interpret the y-intercept in the context of the question: O The best prediction for a game with 0 attendance is that there will be 2 runs scored. O If the attendance of a baseball game is 0, then 2 runs will be scored. O The y-intercept has no practical meaning for this study. O The average runs scored is predicted to be 2.

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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
15
55
23
18
48
26
29
27
21
14
18
11
Runs
7
12
7
1
10
3
7
6
4
a. Find the correlation coefficient: r =
0.71
* Round to 2 decimal places.
b. The null and alternative hypotheses for correlation are:
Ho: pv
H1: pv
The p-value is: 0.0097
(Round to four decimal places)
c. Use a level of significance of a
of the study.
0.05 to state the conclusion of the hypothesis test in the context
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 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 there is a correlation between the
attendance of baseball games and the runs scored. Thus, the regression line is useful.
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.
d. 12
(Round to two decimal places) (Round to two decimal places)
e. Interpret r2:
O There is a 50% chance that the regression line will be a good predictor for the runs scored
based on the attendance of the game.
O Given any fixed attendance, 50% of all of those games will have the predicted number of runs
scored.
O 50% of all games will have the average number of runs scored.
O 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 50%.
f. The equation of the linear regression line is:
y =
x (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 29,000 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 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.
OFor every additional thousand people who attend a game, there tends to be an average
increase of 0.16 runs scored.
i. Interpret the y-intercept in the context of the question:
O The best prediction for a game with 0 attendance is that there will be 2 runs scored.
O If the attendance of a baseball game is 0, then 2 runs will be scored.
O The y-intercept has no practical meaning for this study.
O The average runs scored is predicted to be 2.
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 15 55 23 18 48 26 29 27 21 14 18 11 Runs 7 12 7 1 10 3 7 6 4 a. Find the correlation coefficient: r = 0.71 * Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: Ho: pv H1: pv The p-value is: 0.0097 (Round to four decimal places) c. Use a level of significance of a of the study. 0.05 to state the conclusion of the hypothesis test in the context 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 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 there is a correlation between the attendance of baseball games and the runs scored. Thus, the regression line is useful. 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. d. 12 (Round to two decimal places) (Round to two decimal places) e. Interpret r2: O There is a 50% chance that the regression line will be a good predictor for the runs scored based on the attendance of the game. O Given any fixed attendance, 50% of all of those games will have the predicted number of runs scored. O 50% of all games will have the average number of runs scored. O 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 50%. f. The equation of the linear regression line is: y = x (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 29,000 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 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. OFor every additional thousand people who attend a game, there tends to be an average increase of 0.16 runs scored. i. Interpret the y-intercept in the context of the question: O The best prediction for a game with 0 attendance is that there will be 2 runs scored. O If the attendance of a baseball game is 0, then 2 runs will be scored. O The y-intercept has no practical meaning for this study. O The average runs scored is predicted to be 2.
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