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AP Statistics Final Project. Philadelphia Phillies Attendance. Kevin Carter, Devon Dundore, Ryan Smith. About the Phils. 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 Bank.

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ap statistics final project

AP Statistics Final Project

PhiladelphiaPhilliesAttendance

Kevin Carter, Devon Dundore, Ryan Smith

slide2

About the Phils

  • Oldest one-named, one-city franchise in all professional American sports
  • First game played on May 1, 1883
  • 2 World Series Victories (1980, 2008)
slide3

About the Bank

  • Built in 2004
  • 43,651 seats
  • Sold out 73 times in 2009
  • Biggest attendance 46,208
  • 2008- Celebrated first World Series since 1980
slide4

Studying the Statistics

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
slide5

Tests and Data Analysis cont.

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

slide8

Analysis

Correlation= .04622

Coefficient of Determination= .0021

LSR: Attendance=30.0423(Temperature)+35012

  • Weak (scattered)
  • Very slightly positive

Residual plot is scatter so LSR is a decent fit

data conclusion
Data Conclusion
  • .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
analysis
Analysis

Correlation= -.118

Coefficient of determination= .014

LSR: Attendance= -419.731(Start)+44841

  • Weak (slightly scattered)
  • Slight negative slope

Residual Plot is scatter so LSR is a good fit

data conclusion1
Data Conclusion
  • 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
slide14

Tests and Data Analysis

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)

slide15

Test 1 (temperature)

  • STATE
  • SRS
  • True relationship is linear

CHECK

-Checks out

-Assume (scatter plots)

*Sample size of 60 games

slide16

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.

slide17

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.

test 2 time of day
Test 2 (time of day)

CHECK

-Checks out

-Assume (scatter plots)

STATE

  • SRS

- True relationship is linear

*Sample size of 60 games

slide19

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.

slide20

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.

slide21

Bias/Error

  • 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
personal opinions
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
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.