You’re a realtor with a client in the market for a 3+ bedroom home with at least 2 baths. Randomly sample 10 homes from your original data set from Part A that meet these criteria. Write a report that includes a linear regression model that predicts a home’s listing price based on its size (in square feet). The use of EXCEL or other data software may be beneficial.
- Write an introduction that includes the context of the data and precisely describes the sampling method used to achieve your random sample. Provide a data table that includes the 10 selected homes, their square footage, and their listing price. Calculate the mean and standard deviation for both square footage and price.
- Create a scatterplot showing the association between the two variables. The scatterplot should include the least-squares line and a generic version of the regression equation.
- Describe the association’s direction and form in context of the variables. Describe the strength of the association by providing a calculated correlation coefficient.
- Provide a contextual version of the regression equation. Interpret the slope, intercept, and R2 of the model in context of the two variables.
- Note any outliers or influential points in your scatterplot. Describe what might happen to your model if they were excluded.
- Select one home from your list of 3+ bedroom, 2+ bathroom homes. Interpret the residual associated with this selection. Is the home a good deal, fair deal, or poor deal for your client?
