2. The data below contains sale price, size, and land-to-building ratio for 10 large industrial properties {r} saleprice <- read.csv("https://www.siue.edu/~jpailde/saleprice.csv") saleprice i) Construct a scatterpot for sale price versus size and sale price versus land-to-building ratio`. Be sure to fit regression lines on the scatterplots. ii) Use the `Im function to estimated the equations of each regression model for sale price versus size` and `sale price versus land-to-building ratio`. iii) Check the error model assumption visually by constructing a residual plot and QQplot of the residuals for the two models. iv) Estimate the population regression slope of each model (line) by constructing 95\% confidence interval. Give a brief interpretation of the esimated slope in the context of the problem. v) Perform a hypothesis test on the regression slope of each model (line), use a 5\% level of significance. Given an appropriate conclusion.

MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Can you help me answer this using R code?

2. The data below contains sale price, size, and land-to-building ratio for 10 large
industrial properties
{r}
saleprice <- read.csv("https://www.siue.edu/~jpailde/saleprice.csv")
saleprice
i) Construct a scatterpot for sale price versus size and sale price versus
land-to-building ratio`. Be sure to fit regression lines on the scatterplots.
ii) Use the `Im function to estimated the equations of each regression model for sale
price versus size` and `sale price versus land-to-building ratio`.
iii) Check the error model assumption visually by constructing a residual plot and QQplot
of the residuals for the two models.
iv) Estimate the population regression slope of each model (line) by constructing 95\%
confidence interval. Give a brief interpretation of the esimated slope in the context of the
problem.
v) Perform a hypothesis test on the regression slope of each model (line), use a 5\% level
of significance. Given an appropriate conclusion.
Transcribed Image Text:2. The data below contains sale price, size, and land-to-building ratio for 10 large industrial properties {r} saleprice <- read.csv("https://www.siue.edu/~jpailde/saleprice.csv") saleprice i) Construct a scatterpot for sale price versus size and sale price versus land-to-building ratio`. Be sure to fit regression lines on the scatterplots. ii) Use the `Im function to estimated the equations of each regression model for sale price versus size` and `sale price versus land-to-building ratio`. iii) Check the error model assumption visually by constructing a residual plot and QQplot of the residuals for the two models. iv) Estimate the population regression slope of each model (line) by constructing 95\% confidence interval. Give a brief interpretation of the esimated slope in the context of the problem. v) Perform a hypothesis test on the regression slope of each model (line), use a 5\% level of significance. Given an appropriate conclusion.
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