Build a Housing Simple Linear Regression Model Using SAS Studio

Simple Linear Regression models capture the relationship between a single attribute of a data set (called predictor or independent attribute) and an attribute of the same data set (called target or dependent attribute). Once a simple linear regression model is built, we can use it to predict the unknown value of the target attribute given the known values of its single predictor attribute.

we will use SAS Studio to build a simple linear regression model using the housing data Download housing data also used in Module 2 CT.

To complete this assignment:

Complete these steps:

Step 1:

• Upload the housing.csv file into SAS Studio. Use the Import to transfer the CSV file into a SAS dataset format. Name the resulting data set "housing". Hint: Uncheck the OPTIONS: Generate SAS variable names.
• Take screenshots to demonstrate successful completion of your work. The screenshot should show your SAS Studio selections and the results you obtained. The screenshot should have the current date and time.

Step 2:

• Build a simple linear regression model as follows:
  • Dependent variable: VAR14
  • Continuous variable: VAR1
  • Model effects: use default settings
  • OPTIONS: PLOTS: Diagnostics and Residual Plots: Display as: Individual plots
• Take screenshots to demonstrate successful completion of your work. The screenshot should show your SAS Studio selections and the statistics test results including visual tests you obtained. The screenshot should have the current date and time.

Step 3:

• Write down the equation that relates VAR14 to VAR1.

Step 4:

Summarize your work on this assignment as follows:

• Interpret the statistics test results including visual tests you obtained from your work. Interpretation of results should be relevant and accurate.