Many factors may affect fans' decision to go to a ball game. Is it possible that fans prefer teams with an older pitching staff? 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.

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.

15% chance.

step-by-step explanation:

3/10 times, the 5 year old will get a tablet. 5/10 times, the 13 yer old will get a tablet. multiply both fractions to get 15/100 times, both would have a tablet.