Introducing the Scenario Real Estate can be a highly competitive market, and having every advantage is very important. Margaret Robinson, in addition to billing herself as the Bungee Jumping Real Estate Agent, also invests in statistical investigation in order to improve her position in the market, and do the best job she can for her clients, all with style and class. Margaret has hired you (and your team) to utilize the Redfin website, which provides historical data, in order to ask some important questions about prices and predictions of prices in different areas that she services. You will pick two zip codes, in Washington, to explore in this assignment. You will download data from the Redfin site into Excel. Videos and instructions for how to do this posted on Canvas.

We will be using R to answer these questions. You have received the R Markdown file: HPCaseStudy.Rmd The following variables will be used: Price Bedrooms Bathrooms Square Footage Lot Size Year Built

6) Run a simple regression on Prices and each of the independent variables. Place the table of results below. a. Area #1 b. Area #2

7. a. Is the square foot significant in predicting price in either of your areas? b. How much does the square foot affect the price in each of your areas?

c. In which area does square feet explain more of the variance in price? How do you know?

8. a. Is the number of Beds significant in predicting price in either of your areas? b How much does the number of bedrooms affect the price in each of your areas? c. In which area does the number of bedrooms explain more of the variance in price? How do you know?

9) a. Is the number of Baths significant in predicting price in either of your areas? b. How much does the number of Baths affect the price in each of your areas?

c. In which area does the number of Baths explain more of the variance in price? How do you know?

10) a. Is the Lot Size significant in predicting price in either of your areas? b. How much does the Lot Size affect the price in each of your areas? c. In which area does the Lot Size explain more of the variance in price? How do you know?

11) a. Is the Year Built significant in predicting price in either of your areas? b. How much does the Year Built affect the price in each of your areas? c. In which area does the Year Built explain more of the variance in price? How do you know?

12. What variable would you most likely use to explain price, if you could use only one variable? Area 1: Area 2: