DocumentCode :
3198508
Title :
A regression-based predictive model of student attendance at UVA men´s basketball games
Author :
Walls, Thomas L., Jr. ; Bass, Ellen J.
Author_Institution :
Northrop Grummen Newport News, VA
fYear :
2004
fDate :
16-16 April 2004
Firstpage :
203
Lastpage :
208
Abstract :
A regression-based predictive model was developed to allow better prediction of attendance for the student general admission seats at University of Virginia men´s home basketball games. The goal was to improve upon the existing prediction method that yielded prediction errors sometimes exceeding one thousand students. Based on the existing attendance prediction method and a literature review, twenty candidate factors were identified for potential use in an improved prediction model. Using a best subsets methodology and data from the previous four basketball seasons, a six predictor model was developed with an adjusted R2 value of 0.816. The predictors were based on whether UVA and/or the opponent were ranked, opponent popularity, and whether classes were in session. The resulting model was validated with data from home games from the 2002-2003 season. Its average prediction error of 263 students (standard deviation of 269 students) was a significant improvement over the existing prediction method
Keywords :
educational institutions; prediction theory; regression analysis; sport; UVA men basketball games; University of Virginia; best subsets methodology; literature review; opponent popularity; prediction errors; regression-based predictive model; standard deviation; student attendance; student general admission seats; Cities and towns; Educational institutions; Fans; Mathematical model; Prediction methods; Predictive models; Promotion - marketing; Snow; Standards development; Temperature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems and Information Engineering Design Symposium, 2004. Proceedings of the 2004 IEEE
Conference_Location :
Charlottesville, VA
Print_ISBN :
0-9744559-2-X
Type :
conf
DOI :
10.1109/SIEDS.2004.239907
Filename :
1314681
Link To Document :
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