Assignment 3 data

Assignment 3 data - Assignment 3 Question 1 (A): Fit a...

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Assignment 3 Question 1 (A): Fit a regression model to predict the size of the monthly mortgage or rent payments using all the explanatory variables. Explain whether multicollinearity is a problem. Regression model to predict the size of monthly mortgage is: 0 1 1 2 2 3 3 ... k k y x x x x =β +β +β +β + +β +ε y = 1648.20 + 512.29 x1 + 362.15 x2 + 189.45 x3 – 22.91 x4 + 208.97x5 -0.0034 x6 – 5.54 x7 + 0.12 x8 y = the value of monthly mortgage dependent variable b 0 = the regression constant is 1648.20 b 1 = the partial regression coefficient of independent variable location NW b 2 = the partial regression coefficient of independent variable location SW b 3 = the partial regression coefficient of independent variable location NE b 4 = the partial regression coefficient of independent variable family size b 5 = the partial regression coefficient of independent variable ownership ‘yes’ b 6 = the partial regression coefficient of independent variable income b 7 = the partial regression coefficient of independent variable utilities
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b 8 = the partial regression coefficient of independent variable debt k = the number of independent variables Since, R square is very low and the Y variable isn't strongly correlated with any of the X variables., multicollinearity should not be a problem. Question 1 (B): Fit the best regression model to predict the size of the monthly mortgage or rent payments. Explain why this is the best regression model. We omit family size from the model as it seems less relative. So, The best regression model to predict the size of monthly mortgage is y = 2111.52 + 518.18 x1 + 365.49 x2 + 194.44 x3 + 349.77x4 -0.0036 x5 – 8.04 x6 + 0.12 x7 y = the value of monthly mortgage dependent variable b 0 = the regression constant is 2111.52 b 1 = the partial regression coefficient of independent variable location NW b 2 = the partial regression coefficient of independent variable location SW b 3 = the partial regression coefficient of independent variable location NE b 4 = the partial regression coefficient of independent variable ownership ‘yes’ b 5 = the partial regression coefficient of independent variable income b 6 = the partial regression coefficient of independent variable utilities b 7 = the partial regression coefficient of independent variable debt
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This is the best regression model because when we run regression again without including the family size variable, then all the p values are less than 0.05 and f- value of 19.26 shows significance. Therefore, the variables are now significant and model is best possible fit.
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Assignment 3 data - Assignment 3 Question 1 (A): Fit a...

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