USE RSTUDIO TO ANSWER THE FOLLOWING QUESTIONS. PRESENT R CODES AND SCREENSHOTS OF EVERY OUTPUT WITH THE CODE AND ASSIGN THE QUESTION NUMBER TO THE ANSWER.

Question 1 to 4 has been answered. I JUST NEED HELP ON QUESTIONS 5 TO 8

DATA SET IS HERE: https://docs.google.com/spreadsheets/d/1fthpWnzxx4vljWjuZIzSU4_ShpfzdHMl/edit?usp=sharing&ouid=101981614875951507390&rtpof=true&sd=true

Use the attached dataset HomesforSale.xls which contains a random sample of home prices in 4 different states with 120 observations on the following 5 variables.

State	Location of the home:CANJNYPA
Price	Asking price (in $1,000's)
Size	Area of all rooms (in 1,000's sq. ft.)
Beds	Number of bedrooms
Baths	Number of bathrooms

1. Make a scatterplot of Price and Size and justify an appropriate model using log transformation for these 2 variables (add the graphs on your PDF submission). Which transformation works better for a model with these 2 variables (log-lin/ lin-log/ log-log, use these options, be careful with typos).

> HomesforSale_1_

> View(HomesforSale_1_)

> attach(HomesforSale_1_)

The following objects are masked from HomesforSale_1_ (pos = 3):

Baths, Beds, Price, Size, State

> plot(Price~Size)

6000 O 5000 4000 Price 3000 O O O 2000 O O 1000 O OOOO O O O 2 4 6 7 SizeO O O O O O O log(Price) O O O C OO DO OO LO O O O -0.5 0.0 0.5 1.0 1.5 2.0 log(Size)Residuals vs Fitted 058 80 0 O O OO O O 00 060 O O Residuals O O O O O O O O 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 Fitted values Im(log(Price) ~ log(Size) + Beds + Baths)