The document provides data on 35 used Ford Mustangs being sold by Tom from his new car lot and performs regression analyses to determine the relationships between price and various attributes like age, miles, cylinders in order to help Tom better understand how to competitively price his inventory and maximize profits. Recommendations include focusing on the most significant factors of age, cylinders, and miles in pricing according to the regression models as well as comparing prices to industry sources and offering incentives to customers.

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.