This project concerns a problem of interest in buying a used car.The calling price of used cars will vary depending on a number of quantitative

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

 1 Project

 The purpose of this project is to investigate the predictors affecting the calling price and examine the relationship between the mean calling price E(y) (the price asked for by the owner) of a specific kind of car and the independent variables like:

 1. The number of years since production; e.g. If a car is produced on 2010, then numberofyears = 2020 − 2010 = 10.

 2. The Current Mileage of the car(miles).

 3. Color

 4. Title status

 5. Other predictors, you have investigated, that are relevant to calling price of a used car.

 6. .....

 Collect your sample data from: http://charlotte.craigslist.org/

 or https://www.kaggle.com/orgesleka/used-cars-database

 with sample size n ≥ 40

 2 Format of Your Work

 Your work should be clear and easy to understand, follow the following format:

 1. Statement of The Problem: You need to state your problem here. That is, tell us what your study is about and your purpose of the study.

 2. The Data: You need to specify how you collect the data and summarize your sample data. The following table must be included. 

Obs	X1	X2	X3	...	Y
1
2
3
· · ·	· · ·	· · ·	· · ·	· · ·	· · ·
n

 

Define the variables.

Y :

X₁:

X₂:

X₃:

· · ·

 3. Variable selection: Apply the techniques you have learned in chapter 6 and select (3 to 4) variables that are useful to predict calling price of used car, y.

 4. The Model selection: Propose at least four different models you want to apply and select the best model using partial F test or any other statistical techniques you have learned.

 5. Assumption check: In this part, you will check the model assumption for the model you have selected in part 4 (apply the concepts learned in chapter 8).

 6. Model Remedy: Depending on your findings in step 5, do some transformation for y or x to make the model assumptions be satisfied (if necessary) and write down the new model.Use the concepts learned in Chapter 8.

 7. Model adequacy: Test the adequacy of the final model in part 5 (overall F test).

 8. Conclusion: Provide adjusted R squared, model standard error and explain is this model good to use.

 9. check: find new data for a car that are not used in this model building process and predict its price using your final model. Is the predicted price close to the real price?

 10. Technical Appendices R code: provide the R - codes you have used in this project.

Attachments:

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