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until Nov 18 friday at 5pmstatistix10 software knowledge required.QMB 3200 FALL 2022 Project Submission 3

Complete your work in this document in black type. Leave the existing document in the blue

type it is currently in and do not edit the document except to add your responses below each

prompt. Submit to Canvas as a single doc or docx file; submissions consisting of multiple files or

files submitted in inaccessible formats will not be graded. Check to make sure you submit the

correct file; if you need to re-submit after the due date there will be a penalty of 25%. The

assignment is due by November 18th at 5:00pm; late work will be penalized 10% per day or

portion of a day that it is late. This assignment is worth 45 points. You will use your student

data set (cars) to run all analyses. NOTE: YOU MUST INCLUDE PRINTUTS IN ORDER FOR YOUR

WORK TO BE GRADED. WITHOUT PRINTOUTS, YOUR GRADE WILL BE ZERO.

Refer to the video in Course Kaltura if you have any questions regarding how to correctly

complete this assignment.

Delete one of your vehicle models from your data set, preferably the vehicle that was in

the middle when you ranked your vehicle models by price in Project Submission 2.

Recode the levels of Model Vehicle as 0 for one model and 1 for the other. We will no

longer be using the variable “Year Manufactured” so you can delete that if you want.

Add the quadratic term and the interaction terms. You will then start with the complete

2nd-Order Model and “build down” through the entire model-testing process, until you

have obtained the best-fitting model. Use this to respond to the following items. Refer

to the video in Course Kaltura if you have any questions about what to do to your data

set before you can begin your work.

Complete 2nd-Order Model: E(Y) = β0 +β1×1 + β2×12 +β3×2 +β4x1x2 + β5x12x2

Part 1: Model Building

A.1. Global F Test: run a test of the complete 2nd order model. Insert the STATISTIX

Printout of the results of this test. (3 points)

A.2 Fill in the following information for your Global F test (1 point per response/ total 5

points)

Test: H0:

Ha:

Test Statistic:

P-value:

Conclusion:

B. 1. Quadratics test: run a quadratics test. Insert the STATISTIX Printout of the results

of this test. (3 points).

B.2. Fill in the following information for your quadratics test (1 point per response/ total

7 points)

Full Model:

Reduced Model:

Test: H0:

H a:

Test Statistic:

P-value:

Conclusion:

C.1. Interactions Test: run an interactions test. Insert the STATISTIX Printout of the

results of this test. (3 points)

C.2.Fill in the following information for your interactions test (1 point per

response/total 7 points)

Full Model:

Reduced Model:

Test: H0:

Ha:

Test Statistic: ________________

P-value: ______________

Conclusion:

D. Would your model building be finished after the interaction test you ran in Part C.1.?

Why or why not? (2 points)

Part 2: Final Model Interpretations

A. Identify the least squares prediction equation for your final model after all the

testing was completed. You do not need to include the Printouts of any additional

tests conducted, just the results of the best test. Use the values from the Printout

and write the prediction equation below (use coefficient values, not betas). (3

points)

ŷ=

B. Report and interpret the R2 and the 2s associated with your best model. (4 points)

C. Would you use your model in practice? Why or why not? (3 points)

Part 3: Using the model

A. Using your best model, predict the price and estimate the mean price for Case # 17

in your data set. Insert the STATISTIX Predicted and Fitted Intervals Printout of the

results. (3 points)

B. Interpret the interval for the predicted value. (1 point)

C. Interpret the interval for the fitted value. (1 point)

price

miles

43998

34998

40998

28998

34998

39998

31998

36998

29998

36998

41998

34998

30998

35998

42998

23998

31998

40998

32998

50998

37998

30998

29998

45998

28998

year

14000

64000

54000

46000

26000

19000

36000

38000

20000

63000

42000

32000

78000

17000

14000

75000

57000

11000

35000

5000

51000

22000

35000

12000

78000

model

1

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