# Compare and contrast your sample with the population using the National Statistics and Graphs document.

Scenario:Smart businesses in all industriesuse data to provide an intuitive analysis of how they can get a competitiveadvantage. The real estate industry heavily uses linear regression to estimatehome prices, as cost of housing is currently the largest expense for mostfamilies. Additionally, in order to help new homeowners and home sellers withimportant decisions, real estate professionals need to go beyond showingproperty inventory. They need to be well versed in the relationship betweenprice, square footage, build year, location, and so many other factors that canhelp predict the business environment and provide the best advice to theirclients.
PromptYou have been recently hired as ajunior analyst by D.M. Pan Real Estate Company. The sales team has tasked youwith preparing a report that examines the relationship between the sellingprice of properties and their size in square feet. You have been provided witha Real Estate Data spreadsheet that includes properties sold nationwide inrecent years. The team has asked you to select a region, complete an initialanalysis, and provide the report to the team.Note: In the report you prepare for the sales team, theresponse variable (y) should be the listing price and the predictor variable(x) should be the square feet.Specifically you must address the following rubriccriteria, using the Module Two Assignment Template (attached)·Generate a Representative Sample of the Data·Select a region and generate a simple randomsample of 30 from the data.·Report the mean, median, and standard deviationof the listing price and the square foot variables.·Analyze Your Sample·Discuss how the regional sample created is or isnot reflective of the national market.·Compare and contrast your sample with thepopulation using the National Statistics and Graphs document.·Explain how you have made sure that the sampleis random.·Explain your methods to get a truly randomsample.·Generate Scatterplot·Create a scatterplot of the x and y variablesnoted above and include a trend line and the regression equation·Observe patterns·Answer the following questions based on thescatterplot:oDefine x and y. Which variable is useful formaking predictions?oIs there an association between x and y?Describe the association you see in the scatter plot.oWhat do you see as the shape (linear ornonlinear)?oIf you had a 1,800 square foot house, based onthe regression equation in the graph, what price would you choose to list at?oDo you see any potential outliers in thescatterplot?oWhy do you think the outliers appeared in thescatterplot you generated?oWhat do they represent?