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.
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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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