Regression Equation and Linear Regression Analysis

Question Description

You want to develop aregression model to predict the number of wins achieved byeach NBA team, based on the average point difference and the average field goal percentage difference between the team and itsopponent. Using the Data Analysis add-in, follow the steps listed below and answer the following questions.

6.1Perform multiple linear regression analysis. State the regression equation. 

6.2Interpret the meaning of the slope coefficientsobtained.Explain whether the intercept coefficient hasapractical interpretation or not in the context of this study.

6.3Based on your model, predict wins for a teamwith average point difference of 6, and average field goal % difference of 3.5.

6.4Based  on  the  residual  plots received in  your  model,  comment  on  the plausible satisfaction  of  the normal residual (noise) model assumptions.

6.5 Do you have to use the Durbin-Watson statistic? 

6.6  Repeat  steps  6.1  to  6.4  to  develop  a multiple  linearregression model  that  also  considers  possible interaction between average point difference, and average field goal % difference. Draw your conclusion.

6.7 Based on the results received so far, select and develop a simple linear regression model, repeating steps6.1 to 6.4 for this model. Draw your final conclusion.Submit both your answers summarized in a Word doc file, and your complete Excel solution file. In the Excel file, use the Data Analysis add-in, and store the results in separate (appropriately named)tabs.

TeamWins Points ScoredPoints AllowedPoint DifferenceField Goal%Field Goal % AllowedField Goal % DifferenceOwn TurnoversOpponent TurnoversTurnover DifferenceRebound % 
Atlanta4498.097.50.546.445.01.414.314.6-0.348.3
Boston4196.596.7-0.246.544.12.413.914.4-0.547.5
Brooklyn4996.995.11.845.046.4-1.413.913.00.952.2
Charlotte2193.4102.7-9.342.547.1-4.613.113.6-0.547.8
Chicago4593.292.90.343.744.3-0.613.713.10.651.2
Cleveland2496.5101.2-4.743.447.6-4.213.414.7-1.349.3
Dallas41101.1101.7-0.646.244.51.713.514.0-0.547.9
Denver57106.1101.15.047.844.43.414.715.2-0.552.0
Detroit2994.998.8-3.944.945.9-1.014.613.11.550.2
Golden State 47101.2100.30.945.843.91.914.812.91.951.3
Houston45106.0102.53.546.145.40.715.814.21.651.0
Indiana4994.790.74.043.642.01.614.513.01.552.9
L. A. Clippers56101.194.66.547.844.33.513.815.4-1.651.6
L.A. Lakers45102.2101.01.245.845.30.514.612.42.251.2
Memphis5693.489.34.144.443.50.913.214.7-1.552.2
Miami66102.995.07.949.644.05.613.314.7-1.449.0
Milwaukee3898.9100.4-1.543.545.4-1.913.615.3-1.748.8
Minnesota3195.798.1-2.443.946.8-2.914.115.3-1.249.9
New Orleans2794.197.9-3.844.847.1-2.313.712.71.051.4
New York54100.095.74.344.845.8-1.011.614.5-2.949.3
Oklahoma City60105.796.59.248.142.55.614.614.20.451.7
Orlando2094.1101.1-7.044.846.3-1.514.012.11.950.0
Philadelphia3493.296.5-3.344.445.4-1.012.613.8-1.248.4
Phoenix2595.2101.6-6.444.347.0-2.715.014.80.249.0
Portland3397.5100.7-3.244.847.4-2.614.212.71.549.0
Sacramento28100.2105.1-4.944.747.2-2.514.014.1-0.148.2
San Antonio58103.096.66.448.144.23.914.114.3-0.249.3
Toronto3497.298.7-1.544.645.8-1.213.213.7-0.549.1
Utah4398.098.1-0.145.445.8-0.414.214.10.150.7
Washington2993.295.8-2.643.544.0-0.514.613.90.749.4

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