Regression [Use R program]

Project description
Location is known to be the most influential factor in determining home sales prices. Many factors contribute to the desirability of a location— one of which is the home school district. Yet, even for homes located within the same school district, there is still much variability in the home sales prices.

We are interested in studying the sales prices of single family homes located within a particular [elementary] school district in Goleta (a city near Santa Barbara, California, US). Using 36 home sales transactions from the past 3 years, we extracted the following: sale price (price, in thousands of dollars), number of bedrooms (bed), number of bathrooms (bath), house size (hsz, in ft2), lot size (lsz, in ft2), and year built (yrblt). The resulting data set can be found in the accompanying file data.txt.

Your task is to find the most appropriate regression model for the data provided and write a detailed report of your findings. This report should include the following sections:
1. Background/Introduction
2. Methods & Results
3. Discussion
4. Conclusion
5. Future Direction
6. Appendix (for all your graphs/tables).

Your report needs to be double-spaced, have 12pt font size, have 1 inch margins, and be between 4-5 pages long (Note: maximum 5 pages, not including your Appendix). You can only use R program to analyze the data set and generate graphs. Remember…R only!!! And no citation page needed!!!!