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CE 316: Applied Probability and Statistics in CEE
Homework 8
Due: December 5 at 10:00 PM
Problem 1:
Upload the Neth.CSV data file to google colab. Estimate a linear regression model of number of weekly trips per household as a function of the remaining variables (to the extent possible). In the final model identify which variables contribute to an increase in number of weekly trips and which variables contribute to a decrease in the number of weekly trips.
In estimating a linear regression model these are the steps I want you to do:
• Run multiple linear regression by including all variables
• Check for multi-collinearity and remove appropriate variables.
• Check if all variables are significant and remove the variables which are not significant one by one.
• Report the R2 and Adjusted R2 of the final model
• Check if the mean of the residuals is close to zero. Comment on the mean.
• Plot the histogram of the standardized residuals. Comment on whether the standardized residuals look normal.
• Check for outliers.
• Plot the residuals vs fitted values and comment.
The variable definitions are:
• HHSIZE household size
• NCAR number of cars in household
• HEMPSTS number of workers in household
• HSTUDEN number of students in household
• HTTRPS number of weekly trips per household
• NUCHLT12 number of children < 12 years in household
• CITY household residence in city (dummy variable)
• SUBURB household residence in suburb (dummy variable)
• RURAL household residence in rural area (dummy variable)
• INCOME continuous household income value
• NUCHGT12 number of children >= 12 yrs in household
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