Please help me with Part 3 and Part 4, and show the process in detail, thank u
The Data Collection: On May 18'\Part 2. (5 points) Model Evaluation. a. The model that uses all of the explanatory variables to predict monthly rents is the \"full model". Fit the full model in R. o (0.5 points} Paste the R output for the ll] model. 0 (1 point) State the least squares regression equation of Full Model. 0 (0.5 points} State the adjusted RSquared value. b. The nal model from basic model selection techniques includes the variables rooms, baths, sqrfoot, oampusolose and new. Fit the nal model with these variables in R_ Hint: Jim remove the other variables om the mode! in R. o (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 RSquared value. c. Compare the adjusted R squared values 'om the full model to nal model. 0 (0.5 points) Is there much of a di'erenee? - (0.5 points) \"That 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 mamr Show work . - - - o (2 points) Interpret the point estimate and interval in context h. Interpret the coefcient of the variable new while keeping the other variables constant. 0 {1.5 points) Calculate the 95% condence interval for ns-w. Show work or I . -. o {2 points) Interpret the point estimate and interval in context Part 4. (5 points) Prediction. 3. (2 points} Use the least squares regression equation to predict the monthly rent for a T80 sq. foot house, close to campus with two bedrooms and one bathroom, which does not allow pets and is not new. Note: Yournal model does not have all these variables. Show work or W... h. (1 point) The actual rent of the listing above is $1150. 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 procedwe might you use to come to this conclusion? \fFiles Plots Packages Help Viewer 4 Zoom Export - Publish * C House Indicator and Rent Near Campus and Rent 3000 3000 rent rent 2000 2000 1000 1000 0 0 house campusclose Pets Allowed and Rent New and Rent 3000 3000 rent rent 2000 2000 1000 1000 0 0 pets newCall: Im(formula = rent - rooms + baths + sqrfoot + house + campusclose + pets + new) Residuals: Min 1Q Median 3Q Max -487.19 -155.44 -6.37 139.72 593.40 Coefficients: Estimate Std. Error t value Pr(>It) (Intercept) 45.8343 88.9534 0.515 0.608174 rooms 201.9266 57.4042 3.518 0.000814 * *# baths 187.0469 55.7442 3.355 0.001346 *# sqrfoot 0.5371 0.1075 4.998 4.89e-06 **# house 125.3888 68.3993 1.833 0.071500. campusclose 120.2944 68.5321 1.755 0.084069. pets 5.2202 63.6942 0.082 0.934940 new 192.4080 76.1199 2.528 0.014002 * Signif. codes: 0 '*** 0.001 "** 0.01 '* 0.05 !' 0.1"'1 Residual standard error: 244.5 on 63 degrees of freedom Multiple R-squared: 0.9181, Adjusted R-squared: 0.909 F-statistic: 100.9 on 7 and 63 DF, p-value: It) (Intercept) 40.9468 73.7562 0.555 0.58069 rooms 229.9926 55.8642 4.117 0.00011**# baths 168.9174 55.2633 3.057 0.00325 ** sqrfoot 0.5351 0.1085 4.934 5.89e-06 **# campusclose 145.2099 63.2870 2.294 0.02500* new 189.6607 76.7627 2.471 0.01611 * Signif. codes: ( *** 0.001 '** 0.01'* 0.05 : 0.1" '1 Residual standard error: 2471 on 65 degrees of freedom Multiple R-squared: 0.9137, Adjusted R-squared: 0.9071 F-statistic: 137.7 on 5 and 65 DF, p-value:
