Year Built: Price: Body Type: 2005 5,990 sedan 2006 6,922 sedan 2007 7,500 sedan

Question

Year Built: Price: Body Type: 2005 5,990 sedan 2006 6,922 sedan 2007 7,500 sedan 2008 8,200 sedan 2009 8,750 sedan 2010 8,995 sedan 2011 12,000 sedan 2012 14,500 sedan 2013 15,995 sedan 2014 17,500 sedan 2015 19,750 sedan 2016 22,000 sedan 2017 26,000 sedan 2018 27,500 sedan Year Built: Price: Body Type: 2005 3,590 HatchBack 2006 2,992 HatchBack 2007 6,950 HatchBack 2008 6,495 HatchBack 2009 9,000 HatchBack 2010 10,995 HatchBack 2011 12,500 HatchBack 2012 13,270 HatchBack 2013 12,552 HatchBack 2014 15,000 HatchBack 2015 16,230 HatchBack 2016 20,180 HatchBack 2017 22,400 HatchBack 2018 24,899 HatchBack Year Built: Price: Body Type: 2005 3,250 Coup 2006 4,800 Coup 2007 8,600 Coup 2008 8,899 Coup 2009 9,500 Coup 2010 10,995 Coup 2011 12,535 Coup 2012 16,000 Coup 2013 16,500 Coup 2014 18,000 Coup 2015 21,300 Coup 2016 22,500 Coup 2017 27,930 Coup 2018 28,550 Coup Problem 1. Develop a linear regression model of the price of a used car relative to its age. The age is defined as age (2018-Year built). Use data found at www.autolist.com for years 2005 -2018 Problem2. For the same data use One Way ANOVA to analyze an impact off the car body type on the price. The following three levels of the "body type" are: Sedan, Coupe, and Hatchback Step 1. Create Analysis Data a. b. c. Go to www.autolist.com Select your location and "Make & Model Select any one of your choice ( for example "Ford" or "Acura" or "Toyota") and the Model (e.g. for Acura, select "TL") d. On the next Menu select Year range 2005-2006 Body Type "Sedan" You want to have at least one car for each year. Some years might have more, some less or even Select any one-two cars per year in the range, unavailable. The closer to the year 2018, the more if available. available cars there will be. e. Record data: Year Built, price, Body Type I recommend you to create an Excel file with columns: Year Built, Price, and Body Type and use it for data recording. Comment: Instead of repeating the selection for f. Repeat step e for each year 2-year combination between 2005 and 2018 by small time intervals, you can select a complete changing the Years Range in the selection range at once, but make sure to scroll and get a menu car for each year. g. Repeat steps( e,f, g) for Body Types "Coupe" and then for" Hatchback" h. Record Data i. Compute car age for each car in the sample You do not have to record every single car; just make sure that you have cars for every year in the range. The selection is random. Some years will have more records than others. Some years might have none available!! Step 2. USE THIS DATA to develop linear regression model using MINITAB nswer the following questions 1. 2. 3. 4. Is the model significant at 0.05 significance level? (conduct a test to determine that the true slope differs from 0 or not) What is R sq.? Do you think this model is a good prediction of the price of the used car? Why or why not What is the estimated price ofa 5 year-old car? Step 3. Create 3 groups of data by "Body Type" (Group1: Sedan, Group 2: Coupe Group 3: Hatchback). Use these groups for One Way ANOVA. Make conclusions

Explanation / Answer

1)

data

using excel

data > data analysis -> regression

Result

Price ^ = 25138.2667 - 1713.5282* t

Step- 2

1)
yes, the model is significant as p-value < 0.05

R^2 = 0.9369

for t = 5
y^ = 25138.2667 - 1713.5282* t
= 25138.2667 - 1713.5282* 5
= 16570.6257

Step- 3

One-way ANOVA: Price: versus Body Type:

Method

Null hypothesis         All means are equal
Alternative hypothesis At least one mean is different
Significance level      ? = 0.05

Equal variances were assumed for the analysis.

Factor Information

Factor      Levels Values
Body Type:       3 Coup, HatchBack, sedan

Analysis of Variance

Source     DF     Adj SS           Adj MS     F-Value P-Value
Body Type:   2      40631002     20315501       0.38      0.688
Error          39   2098263397    53801626
Total      41      2138894399

Model Summary

      S R-sq R-sq(adj)    R-sq(pred)
7334.96 1.90%      0.00%       0.00%

Means

Body Type:   N   Mean StDev      95% CI
Coup        14 14954   7998 (10989, 18919)
HatchBack   14 12647   6693 ( 8681, 16612)
sedan       14 14400   7255 (10435, 18365)

Pooled StDev = 7334.96

p-value = 0.688 >0.05

there is not significant price difference betwenn three different body types

Year Built: Price: Body Type: t 2005 5,990 sedan 13 2006 6,922 sedan 12 2007 7,500 sedan 11 2008 8,200 sedan 10 2009 8,750 sedan 9 2010 8,995 sedan 8 2011 12,000 sedan 7 2012 14,500 sedan 6 2013 15,995 sedan 5 2014 17,500 sedan 4 2015 19,750 sedan 3 2016 22,000 sedan 2 2017 26,000 sedan 1 2018 27,500 sedan 0 2005 3,590 HatchBack 13 2006 2,992 HatchBack 12 2007 6,950 HatchBack 11 2008 6,495 HatchBack 10 2009 9,000 HatchBack 9 2010 10,995 HatchBack 8 2011 12,500 HatchBack 7 2012 13,270 HatchBack 6 2013 12,552 HatchBack 5 2014 15,000 HatchBack 4 2015 16,230 HatchBack 3 2016 20,180 HatchBack 2 2017 22,400 HatchBack 1 2018 24,899 HatchBack 0 2005 3,250 Coup 13 2006 4,800 Coup 12 2007 8,600 Coup 11 2008 8,899 Coup 10 2009 9,500 Coup 9 2010 10,995 Coup 8 2011 12,535 Coup 7 2012 16,000 Coup 6 2013 16,500 Coup 5 2014 18,000 Coup 4 2015 21,300 Coup 3 2016 22,500 Coup 2 2017 27,930 Coup 1 2018 28,550 Coup 0

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