Americaspony

America’s Pony Car America’s Pony Car For Sale….For Sale….

Marc KostelanskyMarc Kostelansky

&&

Aniello TambascoAniello Tambasco

Background:Background:

First Introduced to the public by the Ford Motor Company First Introduced to the public by the Ford Motor Company on April 17, 1964 at the New York World’s Fair.*on April 17, 1964 at the New York World’s Fair.*

Created the “ pony car” class of the automotive world –Created the “ pony car” class of the automotive world –coupes with long hoods and short rear decks.*coupes with long hoods and short rear decks.*

The Mustang has been in the lives of the American People The Mustang has been in the lives of the American People for the past forty years acting as a pillar of American for the past forty years acting as a pillar of American lore.**lore.**

It has been Ford’s most famous vehicle since the Model A It has been Ford’s most famous vehicle since the Model A and the best thing is that its success has made it the and the best thing is that its success has made it the companies second model to still be in production.*companies second model to still be in production.*

It was the first car to bring sporty class and style with a It was the first car to bring sporty class and style with a price that most can afford.**price that most can afford.**

*http://en.wikipedia.org/wiki/Ford_Mustang

**http://www.edmunds.com/ford/mustang/history.html

Background Cont.:Background Cont.: Tom has followed his dream on opening a car lot that sells Tom has followed his dream on opening a car lot that sells

vintage and classical cars but he knows little about the vintage and classical cars but he knows little about the business world. He has enrolled in a local community business world. He has enrolled in a local community college to take a few business classes. college to take a few business classes.

Tom is very knowledgeable on the nuts and bolts that Tom is very knowledgeable on the nuts and bolts that makeup the physical features of vintage cars but lacks the makeup the physical features of vintage cars but lacks the skills of the American Business professional.skills of the American Business professional.

Tom has been eyeing the competitors and local Tom has been eyeing the competitors and local advertisement to promote his business and to maximize advertisement to promote his business and to maximize profits but his strategy is not working.profits but his strategy is not working.

Tom’s inability to price his car competitively has caused Tom’s inability to price his car competitively has caused many complaints from customers.many complaints from customers.

How can we help Tom How can we help Tom drive drive

his business to successhis business to success

Data Provided:Data Provided: Tom has provided information on 35 used MustangsTom has provided information on 35 used Mustangs

– Which includes:Which includes: PricePrice Convertible or non-convertibleConvertible or non-convertible AgeAge Miles Miles TransmissionTransmission A/C or no A/CA/C or no A/C 4, 6 or 8 cylinder4, 6 or 8 cylinder GT or non-GT modelGT or non-GT model Privately owned or Dealer ownedPrivately owned or Dealer owned

Mustang Data Table: PRICE CONVERT

AGE MILES TRANS

AIR CYL

GT

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

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

Data Analysis: Simple Linear Data Analysis: Simple Linear RegressionRegression

1.1. Define the variablesDefine the variables

2.2. Describe the relationshipsDescribe the relationships

3.3. Calculate the regression coefficient Calculate the regression coefficient

4.4. How good is the model?How good is the model?

5.5. Is the model significant?Is the model significant?- General null hypothesis - General null hypothesis ββ=0, there is no relationship between x =0, there is no relationship between x and yand y

Regression 1: Price vs. AgeRegression 1: Price vs. Age1.1. Age = x-variable and Price = y-variableAge = x-variable and Price = y-variable

2.2. According to the scatter plot we have a strong negative relationship According to the scatter plot we have a strong negative relationship

Correl. Coeff: 82.1%Correl. Coeff: 82.1%

3.3. Slope: -1393.24 Intercept: 13,727.02Slope: -1393.24 Intercept: 13,727.02

4.4. R squared: 0.6739 Std. Error: 2193.01 p-value: 1.55E-09 t-obs: -R squared: 0.6739 Std. Error: 2193.01 p-value: 1.55E-09 t-obs: -8.25829 8.25829

5.5. There is a strong negative relationship between age and price based on a 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)small p-value and correlation coefficient. Price= 13,727.02-1,393.24(age)

Example : A 6 year old mustang should be priced ~$5,367.58Example : A 6 year old mustang should be priced ~$5,367.58

Regression 2: Price vs. MilesRegression 2: Price vs. MilesAge = x-variable and Price = y-variableAge = x-variable and Price = y-variable

According to the scatter plot we have a weak negative relationship According to the scatter plot we have a weak negative relationship

Correl. Coeff: 56.2%Correl. Coeff: 56.2%

Slope: -0.0917 Intercept: 12,621.69Slope: -0.0917 Intercept: 12,621.69

R squared: 0.5620 Std. Error: 2541.61 p-value: 2.19E-07 t-obs: -6.507R 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 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)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.Example: A mustang with 50,000 miles should be priced ~ $8,036.69.

Regression 3: Price vs. Regression 3: Price vs. Cylinder Cylinder Price = y-variable and Cylinder = x-variablePrice = y-variable and Cylinder = x-variable

According to the scatter plot we have a weak positive relationship According to the scatter plot we have a weak positive relationship

Correl. Coeff: 65.8%Correl. Coeff: 65.8%

Slope: 1362.63 Intercept: -1072.02Slope: 1362.63 Intercept: -1072.02

R squared:0.4338 Std. Error: 2890.79 p-value: 1.72E-05 t-obs: 5.02R 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 There is a weak positive relationship between price and cylinder based on a small p-value and correlation coefficient. Price=-small p-value and correlation coefficient. Price=-1072.02+1362.63(cylinder)1072.02+1362.63(cylinder)

Example: A mustang with 8 cylinders should be priced ~ $9,829.02.Example: A mustang with 8 cylinders should be priced ~ $9,829.02.

Regression 4: Price vs. GT Regression 4: Price vs. GT optionoption

Price = y-variable and GT option= x-variable (0=non-GT & 1= GT)Price = y-variable and GT option= x-variable (0=non-GT & 1= GT)

According to the scatter plot we have a weak positive relationship According to the scatter plot we have a weak positive relationship

Correl. Coeff: 37.2%Correl. Coeff: 37.2%

Slope: 2868.96 Intercept: 7128.27Slope: 2868.96 Intercept: 7128.27

R squared:0.1382 Std. Error: 3565.15 p-value: 0.0279 t-obs: 2.30R 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 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 small p-value and correlation coefficient. Price=7128.27+2868.96(GT option)option)

Example: A mustang with the GT option should be priced ~ $9,997.23Example: A mustang with the GT option should be priced ~ $9,997.23

Regression 5: Price vs. Regression 5: Price vs. TransmissionTransmission

Price = y-variable and Transmission= x-variable (0=manual & 1= auto)Price = y-variable and Transmission= x-variable (0=manual & 1= auto)

According to the scatter plot we have a slight weak negative relationship According to the scatter plot we have a slight weak negative relationship

Correl. Coeff: 14.7%Correl. Coeff: 14.7%

Slope: -1122.57 Intercept: 8867.43Slope: -1122.57 Intercept: 8867.43

R squared:0.022 Std. Error: 3798.38 p-value: 0.3978 t-obs: -0.086R 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 There is a slight weak negative relationship between price and transmission based on the correlation coefficient you accept the null. Price=8867.43-based on the correlation coefficient you accept the null. Price=8867.43-1122.57(Transmission)1122.57(Transmission)

Example: A mustang with an automatic transmission should be priced ~ Example: A mustang with an automatic transmission should be priced ~ $7,744.86.$7,744.86.

Overview: Overview: Significant Relationships (Correlation coefficient) Significant Relationships (Correlation coefficient) -Age (82.1%)-Age (82.1%)

-Cylinder(65.8%)-Cylinder(65.8%)

-Miles (56.2%)-Miles (56.2%)

__________________________________________________________________________________

Non Significant Relationships (Correlation coefficient) Non Significant Relationships (Correlation coefficient) -GT Option (37.2%)-GT Option (37.2%)

-Transmission (14.7%)-Transmission (14.7%)

Recommendations: Recommendations:

Tom should focus his pricing for his used mustangs on the Tom should focus his pricing for his used mustangs on the regression analysis with the significant correlation regression analysis with the significant correlation coefficients (>50%) which are: age, cylinder and miles. coefficients (>50%) which are: age, cylinder and miles.

Tom should also compare his prices using a pricing service Tom should also compare his prices using a pricing service like Kelley Blue Book (like Kelley Blue Book (www.kbb.com) or ) or www.edmunds.com. .

It is highly inaccurate to rely on a gut feeling to price used It is highly inaccurate to rely on a gut feeling to price used mustangs.mustangs.

With every purchase of a mustang Tom should give a $50 With every purchase of a mustang Tom should give a $50 gas card to show customers he appreciated their business.gas card to show customers he appreciated their business.