AP Statistics Final Project

Philadelphia Phillies Attendance

Kevin Carter, Devon Dundore, Ryan Smith

• Oldest one-named, one-city franchise in all professional American sports

• First game played on May 1, 1883

• 2 World Series Victories (1980, 2008)

About the Phils

• Built in 2004• 43,651 seats• Sold out 73 times in

2009• Biggest attendance

46,208• 2008- Celebrated first

World Series since 1980

About the Bank

Studied Phillies attendance from 2004-2009 depending on…

- Weather (temperature) - Time of day

• Calculator randomly select 10 games from each season• Look up time of first pitch and park attendance of past games

using www.baseball-reference.com and www.fairview.ws

Studying the Statistics

Create scatter plots of comparisons to view LSR and correlation

Conduct a 2 sample t confidence interval for each comparison of statistics

Also, conduct a 1 sample t confidence interval of the average attendance at Citizens Bank Park

Tests and Data Analysis cont.

Exploratory Data Analysis

40 50 60 70 80 90 100 11015000

20000

25000

30000

35000

40000

45000

50000

Temperature Vs. Attendance

Temperature (°F)

Atten

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Residual Plot

-20

0

20

20 25 30 35 40 45 50

Attendance (thousands)

Attendance (thousands)

Temperature = 7.11e-05Attendance + 74

Correlation= .04622Coefficient of Determination= .0021LSR: Attendance=30.0423(Temperature)+35012- Weak (scattered)- Very slightly positiveResidual plot is scatter so LSR is a decent fit

Analysis

• .21% of the change in attendance is due to the change in temperature

• Temperature seems to have practically no relationship or effect on Phillies game attendance

Data Conclusion

Exploratory Data Analysis

1 1 10:00

0:00

Start Time Vs. Attendance

Series1

Game Start Time

Atten

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Residual Plot

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-10

0

10

12 14 16 18 20

Start_Time

Start_Time

Correlation= -.118Coefficient of determination= .014LSR: Attendance= -419.731(Start)+44841- Weak (slightly scattered)- Slight negative slopeResidual Plot is scatter so LSR is a good fit

Analysis

• 1.2% of the change in attendance is due to the change in start time of the game

• Start time seems to have practically no relationship or effect on Phillies game attendance

Data Conclusion

Use linear regression t tests for both comparisons to test the hypothesis that…

Beta= 0 or Beta>0 (temperature)

Beta=0 or Beta>0 (time of day)

Tests and Data Analysis

STATE

- SRS- True relationship is

linear

CHECK

-Checks out-Assume (scatter plots)

*Sample size of 60 games

Test 1 (temperature)

t= b/SEb

t= .3524 (df=58)P(t> .3524|df=58)= .36.36>.05 so…We fail to reject the null hypothesis because the

p-value is greater than .05. We have sufficient evidence that the slope of

the LSR line is not greater than zero. The weather does not have a great effect on

Phillies game attendance.

Mean+/- t-score(Stand. Dev. of Stat.)= (35201.9, 39256.2)We are 95% sure that population difference of

means lies between 35201.9 and 39256.2 people attending the game.

STATE- SRS- True relationship is linear

Test 2 (time of day)CHECK-Checks out-Assume (scatter plots)

*Sample size of 60 games

t= b/SEb

t= -.9085 (df=58)P(t>-.9085|df=58)= .82.82>.05 so…We fail to reject the null hypothesis because the

p-value is greater than .05.We have sufficient evidence that the slope of

the LSR line is not greater than zero.The start time of the game does not have a great

effect on the Phillies attendance.

Mean+/- t-score(Stand. Dev. Of Stat.)= (35260, 39314.6)We are 95% sure that the population difference

of means lies between 35260 and 39314.6 people attending the game.

• Attendance can be affected by other things (team being played, pitcher, star ball players, promotions, ticket pricing)

• Phillies were better and more popular during some year than others

• Data included many more night game times than afternoon games

Bias/Error

Personal Opinions

• We would have thought that our data would have a had a better correlation.

• We feel that our own decisions to go to a game is somewhat effected by time and temperature. (Rainy day = colder weather)

• We feel that there was to much bias to our data.

Conclusion

• In conclusion, we can say that time of day and temperature has no relation to the attendance of a Philadelphia Phillies baseball game. Either nothing or something else is effecting the attendance of these games.

Q&A