Many factors may affect fans' decision to go to a ball game. Is it possible that fans prefer teams with an older pitching staf
f? a) Examine a scatterplot of Attend/Game and PitchAge. Check the conditions for regression. b) Do you think there is a linear association between Attendance and Pitcher Age? c) Compute and discuss the regression model.
2 answers:
Answer:
A) The linearity conditions are satisfied.
b) Yes there is positive linear association because attendance per game increases then pitcher age also increases.
c) The pitcher age increases by 1 year the average attendance tend to increase by about 5511 fans.
Step-by-step explanation:
a)
We have to find scatter plot
First enter all data in excel
Select all data ----------> Click on Insert --------> Scatter ------->Click on first graph
We get( check the first attached for the excel computation)
Conditions.
A) The linearity conditions are satisfied.
b) Yes there is positive linear association because attendance per game increases then pitcher age also increases.
c) y : Dependent variable = attendance per game
x : independent variable = pitchers age
We can solve this question using excel.
First enter data into excel.
Click on Data -------> Data Analysis --------> Regression ------->
Input
Input Y Range : select y values
Input X Range :select values of x.
Output Range : select any empty cell
---------> ok
We get ( check the first attached for the excel computation)
The regression equation is
Attendance = - 124506 +5511 x age
Test statistic for slope is 6.797
P-value for test statistic is 0.0000191
The pitcher age increases by 1 year the average attendance tend to increase by about 5511 fans.
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For instance, plug in x = 0 and we get...
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Another example: plug in x = 2
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y = -|2-6| - 6
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y = -10
So the point (2,-10) is on the graph
The idea is to generate as many points as possible so we get an idea of what this thing looks like.
Generate enough points, and you'll get what you see in Figure 1 (see attached image)
Then draw a line through all of the points. The more points you use, the more accurate the drawing. Doing that will generate the blue function curve you see in Figure 2 (also attached)
To generate each of the red points, you'll plug in various x values to get corresponding y values.
For instance, plug in x = 0 and we get...
y = -|x-6| - 6
y = -|0-6| - 6
y = -|-6| - 6
y = -6 - 6
y = -12
So when x = 0, the y value is -12. The x and y value pair up to get (x,y) = (0,-12)
Another example: plug in x = 2
y = -|x-6| - 6
y = -|2-6| - 6
y = -|-4| - 6
y = -4 - 6
y = -10
So the point (2,-10) is on the graph
The idea is to generate as many points as possible so we get an idea of what this thing looks like.
Generate enough points, and you'll get what you see in Figure 1 (see attached image)
Then draw a line through all of the points. The more points you use, the more accurate the drawing. Doing that will generate the blue function curve you see in Figure 2 (also attached)