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| | Subjective analysis by the National Superntedents Association selected, from across the nation, a list of school districts thought to be among the best in the country. To better understand what variables will lead to students attending a 4 year collegte. For each school district the followinhg data were obtained: |
| | City | Average Class Size | Average instructional Spending per Student | Average Teacher Salary | SAT Score | % Taking SAT Test | Attend 4 Year College |
| | Blue Springs, MO | 25 | $ 3,060 | $ 29,359 | 108.30 | 0.08 | 74 |
| | Garden City, HY | 18 | $ 9,700 | $ 51,000 | 997.00 | 0.99 | 77 |
| | Indianapolis, IN | 30 | $ 3,222 | $ 30,482 | 716.00 | 0.42 | 40 |
| | Newport Beach, CA | 26 | $ 4,028 | $ 37,043 | 977.00 | 0.46 | 51 |
| | Novi, MI | 20 | $ 3,067 | $ 39,797 | 980.00 | 0.15 | 53 |
| | Piedmont, CA | 28 | $ 4,208 | $ 37,274 | 1042.00 | 0.91 | 75 |
| | Pittsburgh, PA | 21 | $ 4,884 | $ 37,156 | 983.00 | 0.80 | 66 |
| | Scarsdale, NY | 20 | $ 9,853 | $ 31,555 | 1110.00 | 0.98 | 87 |
| | Wayne, PA | 22 | $ 5,023 | $ 40,406 | 1040.00 | 0.95 | 85 |
| | Weston, MA | 21 | $ 4,680 | $ 39,800 | 1031.00 | 0.99 | 89 |
| | Farmingdale, NY | 22 | $ 6,729 | $ 45,846 | 947.00 | 0.75 | 81 |
| | Mamaroneck, NY | 20 | $ 10,405 | $ 49,625 | 1000.00 | 0.90 | 69 |
| | Mayfield, OH | 24 | $ 5,881 | $ 36,228 | 1003.00 | 0.25 | 48 |
| | Morristown, NJ | 22 | $ 6,300 | $ 37,000 | 972.00 | 0.80 | 64 |
| | New Rochelle, NY | 23 | $ 8,875 | $ 41,650 | 1039.00 | 0.80 | 55 |
| | Newtown Square, PA | 17 | $ 5,313 | $ 38,000 | 963.00 | 0.75 | 79 |
| | Omaha, NB | 23 | $ 4,815 | $ 32,500 | 1059.00 | 0.31 | 81 |
| | Shaker Heights, OH | 23 | $ 4,370 | $ 38,639 | 940.00 | 0.56 | 82 |
| | Using the Stepwise Regression identify the best model. |
| | 1 | Put all the independent variables in the model and Compute an "F" statistic and p-value (Significance F). |
| | 2 | If the calculated Independent Variable p-value is greater than a, remove the largest p-value. Run again. |
| | 3 | Check each independent variable not in the model for p-value less than a. |
| | 4 | Insert valid independent variable not in the model for p-value less than a. |
| | 5 | Stop when no independent variables can be deleted from or added to the model. |
| | Using the Forward Selection Regression identify the best model. |
| | 1 | Compute an "F" statistic and p-value for each independent variable. |
| | 2 | Sort from lowest p-value to highest p-value. |
| | 3 | Using the Variable with the lowest p-value add the next Variable with the lowest p-value. Run again. |
| | 4 | Stop when the p-value for each of the independent variables not in the model is greater than p Value to Enter. |
| | | Note: you cannot remove a variable from the model. |
| | Using the Backward EliminationRegression identify the best model. |
| | 1 | Put all the independent variables in the model and Compute an "F" statistic and p-value (Significance F). |
| | 2 | If the calculated Independent Variable p-value is greater than a, remove the largest p-value. Run again. |
| | 5 | Stop when the p-value for each of the independent variables in the model is less than the p Value to Exit. |
| | Use the "Regression" tool in the "Data" tab and select "Data Analysis" then "Regression" |