Task 1: Tutorial
• Practice R models presented in “R Code for Textbook Examples in Chap 6.pdf.”
• Read R tutorial on “Regression.” The data sets (women.R, mtcars.R and states.R) referenced in the tutorial are included
Problem 1: Concrete Slump Test Data [50 points]
Once you completed tutorial task, perform the following to complete the problem.
• Create a scatterplot matrix of “Concrete Slump Test Data” and select an initial set of predictor variables
• Build a few potential regression models using “Concrete Slump Test Data”
• Perform regression diagnostics using both typical approach and enhanced approach
• Identify unusual observations and take corrective measures
• Select the best regression model
• Fine tune the selection of predictor variables
• Interpret the prediction results
Problem 2: Forest Fire Data [50 points]
Once you completed tutorial task, perform the following to complete the problem.
• Create a scatterplot matrix of “Forest Fire Data” and select an initial set of predictor variables
• Build a few potential regression models using “Forest Fire Data”
• Perform regression diagnostics using both typical approach and enhanced approach
• Identify unusual observations and take corrective measures
• Select the best regression model
• Fine tune the selection of predictor variables
• Interpret the prediction results
Files Included in the Folder:
Homework 4.docx
R Code for Textbook Examples in Chap 6.pdf.
R Tutorial on Regression.pdf
Modeling Slump Flow Concrete.pdf
Concrete Slump Test Data Description.pdf
Concrete Slump Test Data.xlsx
Data mining Approach to Predict Forest Fires.pdf
Forest Fires Data Description.pdf Forest Fires Data.xlsx mtcars.R states.R women.R
