STAT 390 Statistical methods in engineering and science

Assignment Help Applied Statistics

Reference no: EM132389071

STAT 390 Statistical methods in engineering and science

Final Project

Problem 1: The “car data” (on sakai) are observations of cars sold in the North American market. Five variables were collected for each car: Weight, Disp. (the engine displacement in liters), Mileage, Fuel, and Type.

1) Fit the following regression model:

Mileage = a + b1 * weight + b2 * Disp + b3*Fuel + b4*Type+ error

2) Create a new data set which does not contain the "Type" variable. Find the best regression model for this new data set. [Hint: Now we can use PROC REG.]

If you are interested, you can add the option 'SELECTION':

MODEL Mileage = Weight Disp Fuel/SELECTION = backward; /*forward, stepwise*/

3) Preform model checking procedures for the regression model you created in Part 2. For parts 1-3 make sure you have clear titles for the output and labels for the variables.

Problem 2: For this part of the assignment, you must research a SAS procedure that was NOT discussed in the class. Write a Word document introducing the procedure and apply this procedure to a dataset.

Be sure to include the following:

What is the procedure is used for? What are some of the options or methods?

An example dataset (you may find your own dataset or you may pick one from class).

An example using the procedure including code and the output (ie. results).

Attachment:- Car Final Project.rar

Reference no: EM132389071

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