This dataset continues our saga of modeling the price of this popular Honda automobile. The dataset has now been cleaned to remove the columns with the dealership where the car was offered for sale and specific trim. (a) write out your model in econometric notation. Be very precise! (b) using the 93 observations in the dataset, estimate a model where price is a function of age, mileage and trim of the car. Be sure to avoid the dummy variable trap!! Fully report the results of your model. In this case, interpretation of the coefficients on the dummy variables is particularly important. (c) test the hypothesis that the specific trim does not affect the price of a Civic. Be sure to do all parts of the hypothesis test. (please fully describe steps if you are using Excel)
This dataset continues our saga of modeling the price of this popular Honda automobile. The dataset has now been cleaned to remove the columns with the dealership where the car was offered for sale and specific trim. (a) write out your model in econometric notation. Be very precise! (b) using the 93 observations in the dataset, estimate a model where price is a function of age, mileage and trim of the car. Be sure to avoid the dummy variable trap!! Fully report the results of your model. In this case, interpretation of the coefficients on the dummy variables is particularly important. (c) test the hypothesis that the specific trim does not affect the price of a Civic. Be sure to do all parts of the hypothesis test. (please fully describe steps if you are using Excel)
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Question
This dataset continues our saga of modeling the price of this popular Honda automobile. The dataset has now been cleaned to remove the columns with the dealership where the car was offered for sale and specific trim.
(a) write out your model in econometric notation. Be very precise!
(b) using the 93 observations in the dataset, estimate a model where price is a
(c) test the hypothesis that the specific trim does not affect the price of a Civic. Be sure to do all parts of the hypothesis test.
(please fully describe steps if you are using Excel)
| Price | Years Old | KM | EX | EXT | SE | Sport | Touring |
| 6555 | 9 | 290363 | 0 | 0 | 0 | 0 | 0 |
| 9999 | 9 | 142258 | 0 | 0 | 0 | 0 | 0 |
| 10281 | 6 | 132644 | 0 | 0 | 0 | 0 | 0 |
| 12480 | 5 | 167125 | 0 | 0 | 0 | 0 | 0 |
| 12991 | 7 | 57398 | 0 | 0 | 0 | 0 | 0 |
| 12991 | 6 | 93046 | 0 | 0 | 0 | 0 | 0 |
| 12991 | 6 | 93046 | 0 | 0 | 0 | 0 | 0 |
| 12991 | 7 | 134600 | 0 | 0 | 0 | 0 | 1 |
| 13991 | 7 | 63450 | 1 | 0 | 0 | 0 | 0 |
| 13991 | 6 | 116028 | 1 | 0 | 0 | 0 | 0 |
| 14993 | 5 | 120833 | 0 | 0 | 0 | 0 | 0 |
| 15991 | 6 | 54708 | 1 | 0 | 0 | 0 | 0 |
| 15995 | 6 | 101488 | 1 | 0 | 0 | 0 | 0 |
| 15999 | 3 | 90982 | 0 | 0 | 0 | 0 | 0 |
| 16298 | 4 | 78583 | 0 | 1 | 0 | 0 | 0 |
| 16989 | 4 | 41054 | 0 | 0 | 0 | 0 | 0 |
| 16990 | 5 | 66954 | 0 | 0 | 0 | 0 | 0 |
| 16990 | 3 | 173812 | 1 | 0 | 0 | 0 | 0 |
| 16991 | 5 | 51837 | 0 | 0 | 0 | 0 | 0 |
| 16991 | 5 | 59984 | 0 | 0 | 0 | 0 | 0 |
| 16991 | 5 | 79655 | 0 | 0 | 0 | 0 | 0 |
| 16995 | 4 | 110557 | 0 | 1 | 0 | 0 | 0 |
| 17495 | 4 | 77577 | 0 | 0 | 0 | 0 | 0 |
| 17499 | 4 | 81582 | 0 | 0 | 0 | 0 | 0 |
| 17684 | 5 | 47554 | 1 | 0 | 0 | 0 | 0 |
| 17796 | 4 | 82292 | 1 | 0 | 0 | 0 | 0 |
| 17829 | 4 | 61979 | 0 | 0 | 0 | 0 | 0 |
| 17936 | 4 | 77526 | 0 | 0 | 0 | 1 | 0 |
| 17974 | 4 | 80706 | 0 | 0 | 0 | 0 | 0 |
| 17990 | 4 | 50276 | 0 | 0 | 0 | 0 | 0 |
| 17990 | 5 | 69915 | 0 | 1 | 0 | 0 | 0 |
| 17991 | 4 | 46779 | 0 | 0 | 0 | 0 | 0 |
| 17991 | 5 | 67601 | 1 | 0 | 0 | 0 | 0 |
| 17991 | 5 | 70097 | 1 | 0 | 0 | 0 | 0 |
| 17991 | 3 | 72100 | 0 | 0 | 0 | 0 | 0 |
| 17991 | 4 | 77256 | 0 | 0 | 0 | 0 | 0 |
| 17999 | 4 | 46184 | 0 | 0 | 0 | 0 | 0 |
| 18170 | 4 | 39477 | 0 | 0 | 0 | 0 | 0 |
| 18450 | 3 | 71098 | 0 | 0 | 0 | 0 | 0 |
| 18499 | 5 | 39395 | 1 | 0 | 0 | 0 | 0 |
| 18877 | 5 | 56198 | 0 | 0 | 0 | 0 | 0 |
| 18900 | 3 | 56773 | 0 | 0 | 0 | 0 | 0 |
| 18991 | 4 | 28054 | 0 | 0 | 0 | 0 | 0 |
| 18991 | 3 | 34155 | 0 | 0 | 0 | 0 | 0 |
| 18991 | 4 | 41144 | 0 | 0 | 0 | 0 | 0 |
| 18991 | 3 | 43266 | 0 | 0 | 0 | 0 | 0 |
| 18991 | 3 | 58167 | 0 | 0 | 0 | 0 | 0 |
| 18991 | 4 | 89347 | 1 | 0 | 0 | 0 | 0 |
| 18991 | 4 | 90642 | 0 | 1 | 0 | 0 | 0 |
| 18993 | 8 | 47555 | 0 | 0 | 1 | 0 | 0 |
| 18993 | 2 | 67579 | 0 | 0 | 0 | 0 | 0 |
| 18999 | 4 | 52891 | 1 | 0 | 0 | 0 | 0 |
| 19499 | 2 | 81364 | 1 | 0 | 0 | 0 | 0 |
| 19593 | 5 | 50353 | 0 | 0 | 0 | 0 | 1 |
| 19635 | 3 | 13524 | 0 | 0 | 0 | 0 | 0 |
| 19799 | 5 | 46000 | 0 | 0 | 0 | 0 | 1 |
| 19807 | 3 | 34215 | 0 | 0 | 1 | 0 | 0 |
| 19890 | 5 | 50517 | 0 | 0 | 0 | 0 | 1 |
| 19900 | 3 | 44548 | 0 | 0 | 0 | 0 | 0 |
| 19990 | 4 | 24948 | 1 | 0 | 0 | 0 | 0 |
| 19990 | 4 | 95283 | 0 | 0 | 0 | 1 | 0 |
| 19995 | 3 | 50563 | 0 | 0 | 1 | 0 | 0 |
| 19998 | 4 | 26555 | 1 | 0 | 0 | 0 | 0 |
| 19998 | 3 | 76404 | 1 | 0 | 0 | 0 | 0 |
| 19999 | 2 | 37705 | 0 | 0 | 0 | 0 | 0 |
| 20450 | 3 | 50725 | 0 | 0 | 1 | 0 | 0 |
| 20484 | 3 | 62759 | 0 | 0 | 1 | 0 | 0 |
| 20493 | 3 | 45501 | 0 | 0 | 1 | 0 | 0 |
| 20550 | 3 | 18405 | 0 | 0 | 0 | 0 | 0 |
| 20991 | 2 | 13547 | 0 | 0 | 0 | 0 | 0 |
| 20991 | 4 | 26876 | 0 | 0 | 0 | 0 | 0 |
| 20991 | 3 | 35009 | 0 | 0 | 1 | 0 | 0 |
| 20991 | 5 | 55650 | 0 | 0 | 0 | 0 | 1 |
| 20991 | 5 | 58787 | 0 | 0 | 0 | 0 | 1 |
| 20993 | 4 | 79000 | 0 | 0 | 0 | 0 | 1 |
| 20995 | 2 | 16561 | 0 | 0 | 0 | 0 | 0 |
| 20995 | 3 | 41690 | 0 | 1 | 0 | 0 | 0 |
| 21495 | 3 | 21056 | 1 | 0 | 0 | 0 | 0 |
| 21993 | 3 | 19415 | 1 | 0 | 0 | 0 | 0 |
| 21995 | 3 | 19272 | 0 | 1 | 0 | 0 | 0 |
| 22450 | 4 | 43588 | 0 | 0 | 0 | 0 | 1 |
| 22592 | 2 | 25372 | 1 | 0 | 0 | 0 | 0 |
| 22858 | 3 | 26712 | 0 | 0 | 0 | 1 | 0 |
| 22962 | 3 | 45559 | 0 | 0 | 0 | 0 | 1 |
| 22991 | 3 | 33261 | 1 | 0 | 0 | 0 | 0 |
| 23993 | 3 | 32610 | 0 | 0 | 0 | 0 | 1 |
| 23995 | 1 | 230 | 0 | 0 | 0 | 0 | 0 |
| 24991 | 3 | 17909 | 0 | 0 | 0 | 0 | 1 |
| 24991 | 2 | 20580 | 1 | 0 | 0 | 0 | 0 |
| 24991 | 3 | 23894 | 0 | 0 | 0 | 0 | 1 |
| 24993 | 1 | 9535 | 0 | 0 | 0 | 1 | 0 |
| 25888 | 3 | 30508 | 0 | 0 | 0 | 1 | 0 |
| 26995 | 1 | 3991 | 0 | 0 | 0 | 1 | 0 |
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