Question: Please help me. the code is given by the question(see code comments to change or add sth) The Data Collection: On May 18Part 2. {5

Please help me. the code is given by the question(see code comments to change or add sth)

Please help me. the code is given by the question(see code commentsto change or add sth) The Data Collection: On May 18"\Part 2.{5 points) Model Evaluation. :1. The model that uses all of the

The Data Collection: On May 18"\Part 2. {5 points) Model Evaluation. :1. The model that uses all of the explanatory variables to predict monthly rents is the \"full model\". Fit the full model in R. 0 (0.5 points) Paste the R output for the full model. 0 (1 point) State the least squares regression equation of Full Model. 0 (0.5 points) State the adjusted R-Squared value. b. The nal model from basic model selection techniques includes the variables rooms, baths, sqrfoot. campusclose and new. Fit the nal model with these variables in R. Hint: Just remove the other variables from the model in R. I! (0.5 points) Paste the R output for the nal model. 0 (1 point) State the least squares regression equation of the Final Model. 0 (0.5 points) State the adjusted R-Squared value. c. Compare the adjusted R squared values from the full model to nal model. i (0.5 points) Is there much of a difference? 0 (0.5 points) What does this comparison tell us about the t of two models? Part 3. {7 Points) Model interpretation. a. Interpret the coefcient of number of rooms while keeping the other variables constant. 0 (1.5 points) Calculate the 95% condence interval for mam. Show work or paste R Output. Ir (2 points) Interpret the point estimate and interval in context. b. Interpret the coefficient of the variable new while keeping the other variables constant. 0 (1.5 points) Calculate the 95% condence interval for mw. Show work or paste R Output. Ir (2 points) Interpret the point estimate and interval in context. Part 4. {5 points) Prediction. a. (2 points) Use the least squares regression equation to predict the monthly rent for :1 78C! sq. foot house, close to campus with two bedrooms and one bathroom, which does not allow pets and is not new. Note: Youraal model does not have all these variables. Show work or paste R Output! b. (1 point) The actual rent of the listing above is $1 150. How far off is the nal model at predicting the rent for this listing? In other words, calculate the residual. Show work. c. (2 points} Based on the analysis of the data, is $1150 a reasonable amount to ask for this dwelling? Specically, what procedure might you use to come to this conclusion

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