one economic project

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ECON 335 Final Project Please follow the instructions for this project and select the appropriate techniques that you have learned in this class in order to answer the following questions. Points will be deducted if the submission does not follow the following format: Use only clean sheets of good quality 8 1/2" x 11" white paper. Text should be typed on one side only. Do not put any perfume or cologne on the sheets, neither try to decorate the sheets of paper; remember, it's an academic piece of writing. A title page is essential. Pages should be consecutively numbered, with numbers put in the upper right hand corner, flush with the right margin and 1/2" from the top with 12 font size and 1.5 spacing. Total points = 100 points (2 problems @ 50pts each) Problem-1 The data in Used Cars represent characteristics of cars that are currently part of an inventory of a used car dealership. The variables included are car, year, age, price ($), mileage, power(hp), fuel (mph), Region of origin (manufactured in USA or in a foreign country), and single ownership (Yes= owned by one or No= owned by more than one owner). The excel file for this problem is stored in Canvas under module called “Used Cars”. You want to describe each of these variables, and you would like to predict the price of the used cars. Make sure to take appropriate steps to analyze this data set and write a mini report for the Car Dealer. Also, do you think that the model is missing some important variables? If so, what are those missing variables? Please explain. (50 points) Use the UsedCars.xlsx dataset on Canvas to answer the following questions. This dataset represents characteristics of cars that are currently part of the inventory at a used car dealership. The variables included are car, year, age, price ($), mileage, power (hp), fuel (mph), region of origin (manufactured in USA or elsewhere), and single ownership (yes = owned by one owner, no = owned by more than one owner). The owner of the dealership is interested in whether there is a relationship between the price of a car and the age of the car. Specifically, he’s interested in whether car age can predict car price. 1. Based on the information above, develop the appropriate hypothesis regarding the relationship between price and age. 2. Write out the univariate regression equation designating price as the dependent variable, estimate the equation from question 1, and report the results. Based upon these results, what is the relationship between car price and age? In the provided dataset, there are other variables besides car price and age. The dealership owner thinks that mileage, power and origin region may also predict price. 1 ECON 335 Final Project 3. Do you believe these other variables could be helpful in predicting price? Determine the appropriate regression equation for predicting price using these additional variables. Report the results of your multivariate regression equation. Based upon your new results, what is the relationship between car price and age? Problem-2 The owner of a moving company typically has his most experienced manager predict the total number of labor hours that will be required to complete an upcoming move. This approach has proved useful in the past, but the owner has the business objective of developing a more accurate method of predicting labor hours. In a preliminary effort to provide a more accurate method, the owner has decided to use the number of cubic feet moved and whether there is an elevator in the apartment building as the independent variables. He has collected data for 36 moves in which the origin and destination were the borough of Manhattan in New York City and the travel time was an insignificant portion of hours worked. The data are organized and stored in Moving. Follow the appropriate steps, 2 ECON 335 Final Project like hypothesis(s), test statistics, critical value/P-value, decision and conclusion to complete the questions. Please insert Excel outputs in your answer(s) wherever it is necessary. (50 points) a. Identify the problem and define the research question(s). b. State the appropriate multiple regression equation for predicting labor hours, using the number of cubic feet moved and whether there is an elevator. c. Interpret the regression coefficients in(a) and evaluate your hypothesis(es). d. Check the regression model validity e. Is there a significant relationship between labor hours and the two independent variables (cubic feet moved and whether there is an elevator in the apartment building) at the 0.05 level of significance? f. At the 0.05 level of significance, determine whether each independent variable makes a contribution to the regression model. Indicate the most appropriate regression model for this set of data. g. Predict the mean labor hours for moving 500 cubic feet. What should you tell the owner of the moving company about the relationship between cubic feet moved and labor hours? h. Construct 95% confidence interval estimate of the population slope for the relationship between labor hours and cubic feet moved. i. Compute and interpret adjusted r2. j. Add an interaction term to the model, and at the 0.05 level of significance, determine whether it makes a significant contribution to the model. k. On the basis of the results of (g) and (j), which model is most appropriate? Explain. l. As a business owner, what conclusions/solutions can you reach concerning the effect of the number of cubic feet moved and whether there is an elevator on labor hours? 3
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This is great! Exactly what I wanted.

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