7/14/09-Chapter Presentation

1. America’s Pony Car For
Sale….
Marc Kostelansky
&
Aniello Tambasco

2. Background:
 First Introduced to the public by the Ford Motor Company on April
17, 1964 at the New York World’s Fair.*
 Created the “ pony car” class of the automotive world –coupes
with long hoods and short rear decks.*
 The Mustang has been in the lives of the American People for the
past forty years acting as a pillar of American lore.**
 It has been Ford’s most famous vehicle since the Model A and the
best thing is that its success has made it the companies second
model to still be in production.*
 It was the first car to bring sporty class and style with a price that
most can afford.**
*http://en.wikipedia.org/wiki/Ford_Mustang
**http://www.edmunds.com/ford/mustang/history.html

3. Background Cont.:
 Tom has followed his dream on opening a car lot that sells vintage
and classical cars but he knows little about the business world. He
has enrolled in a local community college to take a few business
classes.
 Tom is very knowledgeable on the nuts and bolts that makeup the
physical features of vintage cars but lacks the skills of the American
Business professional.
 Tom has been eyeing the competitors and local advertisement to
promote his business and to maximize profits but his strategy is not
working.
 Tom’s inability to price his car competitively has caused many
complaints from customers.

4. How can we help Tom drive
his business to success

5. Data Provided:
 Tom has provided information on 35 used Mustangs
– Which includes:
 Price
 Convertible or non-convertible
 Age
 Miles
 Transmission
 A/C or no A/C
 4, 6 or 8 cylinder
 GT or non-GT model
 Privately owned or Dealer owned

6. Mustang Data Table:
AI G
PRICE CONVERT AGE MILES TRANS R CYL T OWNER
$ 12,688.00 0 1 8,200 1 1 8 1 1
$ 11,650.00 0 1 3,000 1 1 8 1 1
$ 9,500.00 0 3 22,000 1 0 8 0 0
$ 12,500.00 0 2 23,800 1 1 8 1 1
$ 10,488.00 1 4 20,000 1 1 8 1 1
$ 5,988.00 0 4 37,000 1 1 4 0 1
$ 3,590.00 0 5 55,000 1 0 4 0 0
$ 2,800.00 0 6 62,000 1 1 4 0 0
$ 4,900.00 0 7 60,000 1 1 8 1 0
$ 13,500.00 1 3 23,000 1 1 8 1 0
$ 12,000.00 0 3 89,000 1 1 8 1 1
$ 4,388.00 0 4 80,000 1 1 4 0 1
$ 3,000.00 0 7 95,000 1 1 4 0 0
$ 3,900.00 0 8 90,000 1 1 8 1 0
$ 3,350.00 0 8 91,000 1 1 8 1 0
$ 10,500.00 0 3 17,000 1 1 8 1 0
$ 6,500.00 0 3 73,000 1 1 8 0 0
$ 12,900.00 1 2 19,000 1 1 8 0 0
$ 9,000.00 0 2 32,000 1 1 8 0 0

7. Mustang Data Cont.:
$ 7,000.00 0 6 56,000 1 1 8 1 0
$ 2,500.00 0 6 92,000 1 1 4 0 0
$ 11,500.00 0 1 27,000 0 1 8 0 0
$ 10,995.00 1 2 27,000 0 1 8 0 1
$ 6,200.00 0 3 55,000 0 1 4 0 0
$ 8,700.00 0 3 25,000 0 1 8 0 0
$ 7,288.00 1 5 84,000 0 1 4 0 1
$ 6,995.00 1 7 78,000 0 1 4 0 0
$ 2,488.00 0 7 67,000 0 1 4 0 1
$ 4,200.00 1 8 65,000 0 1 6 0 0
$ 12,990.00 1 1 13,300 0 1 8 0 1
$ 14,500.00 1 3 31,000 0 1 8 1 0
$ 10,900.00 1 3 4,000 0 1 8 0 1
$ 8,500.00 0 3 34,000 0 1 8 0 0
$ 12,988.00 0 1 21,000 0 1 8 1 1
$ 5,900.00 0 4 110,000 0 1 8 0 0
0=Convertible 0=manual 0=No A/C 0=Not GT 0=Dealer Owner
1=Not Convertible 1=auto 1=A/C 1=GT 1=Private Owner

8. Data Analysis: Simple Linear
Regression
§ Define the variables
§ Describe the relationships
§ Calculate the regression coefficient
§ How good is the model?
§ Is the model significant?
- General null hypothesis β=0, there is no relationship between x and y

9. Regression 1: Price vs. Age
n Age = x-variable and Price = y-variable
n According to the scatter plot we have a strong negative relationship
Correl. Coeff: 82.1%
13. Slope: -1393.24 Intercept: 13,727.02
15. R squared: 0.6739 Std. Error: 2193.01 p-value: 1.55E-09 t-obs: -8.25829
17. There is a strong negative relationship between age and price based on a small p-
value and correlation coefficient. Price= 13,727.02-1,393.24(age)
Example : A 6 year old mustang should be priced ~$5,367.58

10. Regression 2: Price vs. Miles
Age = x-variable and Price = y-variable
According to the scatter plot we have a weak negative relationship
Correl. Coeff: 56.2%
Slope: -0.0917 Intercept: 12,621.69
R squared: 0.5620 Std. Error: 2541.61 p-value: 2.19E-07 t-obs: -6.507
There is a weak negative relationship between miles and price based on a small p-value
and correlation coefficient. Price=12.621.69-0.0917(miles)
Example: A mustang with 50,000 miles should be priced ~ $8,036.69.

11. Regression 3: Price vs. Cylinder
Price = y-variable and Cylinder = x-variable
According to the scatter plot we have a weak positive relationship
Correl. Coeff: 65.8%
Slope: 1362.63 Intercept: -1072.02
R squared:0.4338 Std. Error: 2890.79 p-value: 1.72E-05 t-obs: 5.02
There is a weak positive relationship between price and cylinder based on a small p-value
and correlation coefficient. Price=-1072.02+1362.63(cylinder)
Example: A mustang with 8 cylinders should be priced ~ $9,829.02.

12. Regression 4: Price vs. GT option
Price = y-variable and GT option= x-variable (0=non-GT & 1= GT)
According to the scatter plot we have a weak positive relationship
Correl. Coeff: 37.2%
Slope: 2868.96 Intercept: 7128.27
R squared:0.1382 Std. Error: 3565.15 p-value: 0.0279 t-obs: 2.30
There is a weak positive relationship between price and GT option based on a small p-
value and correlation coefficient. Price=7128.27+2868.96(GT option)
Example: A mustang with the GT option should be priced ~ $9,997.23

13. Regression 5: Price vs. Transmission
Price = y-variable and Transmission= x-variable (0=manual & 1= auto)
According to the scatter plot we have a slight weak negative relationship
Correl. Coeff: 14.7%
Slope: -1122.57 Intercept: 8867.43
R squared:0.022 Std. Error: 3798.38 p-value: 0.3978 t-obs: -0.086
There is a slight weak negative relationship between price and transmission based on the
correlation coefficient you accept the null. Price=8867.43-1122.57(Transmission)
Example: A mustang with an automatic transmission should be priced ~ $7,744.86.

14. Overview:
Significant Relationships (Correlation coefficient)
 -Age (82.1%)
 -Cylinder(65.8%)
 -Miles (56.2%)
_________________________________________
Non Significant Relationships (Correlation coefficient)
 -GT Option (37.2%)
 -Transmission (14.7%)

15. Recommendations:
 Tom should focus his pricing for his used mustangs on the
regression analysis with the significant correlation coefficients
(>50%) which are: age, cylinder and miles.
 Tom should also compare his prices using a pricing service like
Kelley Blue Book (www.kbb.com) or www.edmunds.com.
 It is highly inaccurate to rely on a gut feeling to price used
mustangs.
 With every purchase of a mustang Tom should give a $50 gas card
to show customers he appreciated their business.