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Major League Baseball - Case Study

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Regression Analysis & Inferences

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Major League Baseball - Case Study

  1. 1. CASE STUDY Submitted to Prof. Manish Thaker Presented by Group 10 Darshit Paun 20131010 Manit Brahmbhatt 20131020 Nisarg Shah 20131030 Raman Shahi 20131040 Shirshendu Mandal 20131050 Vishant Saini 20131060 QUANTITATIVE MANAGEMENT I
  2. 2. -100 0 100 200 300 400 500 600 700 800 Value Revenue Income Chart Value Revenue Income
  3. 3. Value Revenue Income Mean 286.3 119.4333 2.473333 Median 266.5 118.5 3.85 Mode - 108 9.5 Standard Deviation 129.76187 33.05922 10.67339 Variance 16838.143 1130.599 117.8496 Minimum 108 63 -29.6 Maximum 730 215 18.8
  4. 4. -40 -30 -20 -10 0 10 20 30 0 100 200 300 400 500 600 700 800 VALUE-INCOME
  5. 5. Regression Statistics Multiple R 0.185700218 R Square 0.034484571 Adjusted R Square 1.87691E-06 Standard Error 131.9800601 Observations 30
  6. 6. 0 2 4 6 8 10 12 14 16 18 20 0 100 200 300 400 500 600 700 800 VALUE-INCOME (POSITIVE)
  7. 7. Regression Statistics Multiple R 0.534292835 R Square 0.285468833 Adjusted R Square 0.243437588 Standard Error 87.37173983 Observations 19
  8. 8. 0 50 100 150 200 250 0 100 200 300 400 500 600 700 800 VALUE-REVENUE
  9. 9. Regression Statistics Multiple R 0.964709535 R Square 0.930664486 Adjusted R Square 0.928188218 Standard Error 35.36768078 Observations 30
  10. 10. • Value-Income relationship is not significant. • It appears that value is the strongest predictor of revenue. • There is a significant relationship between value and income if the teams incurring losses are ignored from our analysis. • The relationship between value and revenue is significant.

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