clean sheets of good quality 8 1/2" x 11" white paper, economics homework help

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Economics

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Use only clean sheets of good quality 8 1/2" x 11" white paper. Text should be typed on one side only. Do not put any perfume or cologne on the sheets, neither try to decorate the sheets of paper; remember, it's an academic piece of writing. A title page is essential. Pages should be consecutively numbered, with numbers put in the upper right hand corner, flush with the right margin and 1/2" from the top with 12 font size and 1.5 spacing.


The data in Used Cars represent characteristics of cars that are currently part of an inventory of a used car dealership. The variables included are car, year, age, price($), mileage, power(hp), fuel (mph), Region of origin (manufactured in USA or in a foreign country), and single ownership (Yes= owned by one or No= owned by more than one owner). The excel file for this problem is stored under module called “Used Cars”. You want to describe each of these variables, and you would like to predict the price of the used cars. Make sure to take appropriate steps to analyze this data set and write a mini report for the Car Dealer. Also, do you think that the model is missing some important variables? If so, what are those missing variables? Please explain.

And a file is about the data.

Other two files are two examples about the assignment, do not copy!

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Explanation & Answer

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Running Head: USED CAR PROJECT

1

Used Car Project
Name
Institution
Date

USED CAR PROJECT

2
Report on Determinants of Used Car Prices

Determinants of any used prices are numerous. This report, therefore, presents a discussion
of the most significant factors based on statistical analysis. To come up with a reliable conclusion,
a sample of 500 used cars at a dealer shop was selected, and data on the selected sample was
collected. Both qualitative and quantitative data were collected. The quantitative data collected
included the price of the car, year of manufacture and hence the age of the car, mileage covered so
far, power and fuel. Qualitative data included information about whether the car was manufactured
in the United States or a foreign country and whether the car was owned by a single person or more
than one person.
From the data collected, y-variable is the price of the used car. This is because it is the
dependent variable whereas the rest of the variables were considered x-variables because they in
one way or another influences the price. To understand the significance and relationship between
the dependent and the independent variable, a regression analysis was performed. But before
running the regression analysis, the data was analyzed using descriptive statistics.
As mentioned above, the data collected had both quantitative data and qualitative data. To
make qualitative data quantitative, the data was coded using the integer 1 and 0 (McNeil &
Chapman, 2005; Carlberg, 2014). For origin, those cars manufactured in the US were coded 1
whereas those manufactured in a foreign country were coded 0. Similarly, those cars that were
initially owned by a single person were recorded 1 while those with more than one owner were
coded 0. Coding make analyzing quantitative data possible.

USED CAR PROJECT

3
Descriptive Data

Price
Mean
Standard
Error
Median
Mode
Standard
Deviation
Minimum
Maximum
Sum
Count

Age

Mileage

Power
(HP)

Fuel
(MPG)

Region
of
Single
origin owner

9057.80

8.36

92492.00

174.78

25.47

0.71

0.67

93.44
9100.00
10600.00

0.21
8.00
3.00

2303.83
91000.00
40000.00

1.34
180.00
130.00

0.42
27.00
12.00

0.02
1.00
1.00

0.02
1.00
1.00

2089.47
4800.00
13400.00
4528900.00
500.00

4.79
1.00
16.00
4181.00
500.00

51515.22
5000.00
184000.00
46246000.00
500.00

29.92
130.00
220.00
87390.00
500.00

9.44
12.00
42.00
12735.00
500.00

0.46
0.47
0.00
0.00
1.00
1.00
353.00 334.00
500.00 500.00

From the descriptive statistics above, it’s apparent that the sample consists of 353 cars
manufactured in the US and 147 from foreign countries. The sample was also made up of 334
single owned cars, and 166 non-single owned cars. The statistics also shows the average price of
a used car to be $9,057.80, and we can also say that based on the sample, the vehicles in the dealer
shop are between a year old to 16 years old with the most cars being 3 years old. Furthermore, we
can say that the largest mileage covered by the cars in the shop is 184,000miles while the smallest
mileage is 5,000 miles and most vehicles have actually covered 4,000 miles. The descriptive
statistics gives an overview of the sample data. Therefore, to comprehensively analyze the data
and use this analysis to make inference about the entire population, there was a need for performing
a regression analysis.

USED CAR PROJECT

4
Regression Analysis

Regression analysis is a statistical technique that is used determines the relationship
between variables (Cowan, 2004). Regression analysis results normally have three with the main
metric being the intercept, the coefficient, the R-squared, the adjusted R-squared and the p-value.
Before using the regression analysis results to form a regression model, there was the need to
determine if all the variables were statistically significant (Cowan, 2004). A variable is considered
significant if its p-value is less than the significance level used in the regression analysis (Wang &
Jain, 2003). The results below shows part three of the regression analysis result and it was used to
determine the significance of the variable.

Intercept
Year
Age
Mileage
Power (HP)
Fuel (MPG)
Region of origin
Single owner

Coefficients
Standard Error
12953.32793
768.6667128
0
0
-285.1267654
46.32344455
-0.012553909
0.004304894
-8.370190934
8.111615837
42.6670949
25.7252244
-28.59946237
52.29839736
69.22228311
50.44309571

t Stat
16.85168319
65535
-6.155128752
-2.916194718
-1.031877138
1.658570368
-0.546851602
1.372284594

P-value
1.18357E-50
0
0
0.003704752
0.302635614
0.097838437
0.584728116
0.170598887

Based on the results above, only mileage and age are significant. I have intentionally left
year because the year of manufacture determines the how old a car is. The rest of the variables
have p-value more than a significance level of 0.05. However, it would not be prudent to eliminate
all the variables with a p-value greater than 0.05 at once. We, therefore, eliminated the variables
one at a time starting with one that has the highest p-value. As highlighted above, the region of
origin is the least significant and therefore it was eliminated, and a regression analysis performed

USED CAR PROJECT

5

again. This step was repeated until a result with variables' p-value less than 0.05 was found. The
final regression results were, therefore, has shown below.
Part 1
Regression Statistics
Multiple R
0.96742
R Square
0.93589
Adjusted
R
Square
0.93349
Standard Error
530.636
Observations
500
Part 2
ANOVA
df
Regression
Residual
Total

4
496
500

SS
2038918613
139660967
2178579580

Coefficients
12192.3
0
-292.91
-0.0118
16.1198

Standard
Error
81.31208179
0
46.08750159
0.004284727
2.532104958

MS
509729653
281574.53

F
2413.711

Significance
F
0

Part 3

Intercept
Year
Age
Mileage
Fuel (MPG)

t Stat
149.943992
65535
-6.3555889
-2.764776
6.36616152

P-value Lower 95%
0
12032.5
0
0
0
-383.464
0.0059
-0.02026
0.0000
11.14481

Upper
95%
12352.02
0
-202.362
-0.00343
21.09476

Part 1 of the regression analysis above consist of five metrics namely the multiple R, Rsquared, adjusted R-squared, observations and standard error. The multiple R metrics measures
the strength of the linear relationship between the variables (Wang & Jain, 2003). Based on our
sample data, the multiple R is 0.9674 showing a very strong correlation between the age, mileage,

USED CAR PROJECT

6

fuel, and price of a used car. The second metric is the R-squared, and it shows what percentage of
the variation in the y-variable is explained by the x-variable (McNeil & Chapman, 2005). From
the analysis above, it is apparent that 93.59% of the variation in used car prices is explained by
variation in age of the car, mileage covered and fuel. The R-squared is mostly relied upon when
the regression is has a single independent variable. However, where the regression involves
multiple x-variables, then adjusted R-squared is preferred (McNeil & Chapman, 2005). The sample
adjusted R-squared is 0.9335 meaning 93.35% of the variation in the used car price is explained
by a variation in the car’s age, mileage and fuel consumption. The other two metrics in this section
are the standard error and the observation. Observation shows the sample size while the standard
error is basically used to test whether the coefficient is different from zero.
The second part of the regression analysis is the sample ANOVA. This section is made of
the degree of freedom, the sum of residuals and the sample f-test. This section is not commonly
utilized, and for this project, it won't be utilized either.
The third and last part of the regression analysis is the intercept and the coefficient section.
This section is made up of the intercept coefficient and the x-variable coefficient. The section also
entails the p-value, t-statistics, lower limit and the upper limit (Carlberg, 2014). The p-value has
been discussed above, and it shows the statistical significance of a variable. The upper and lower
limit indicates the confidence interval of a variable. The most important metric in this section is
the coefficient. The variable coefficient shows the average change in the car price given a unit
change in the x-variable while holding other x-variable constant (Carlberg, 2014). A positive
coefficient indicates a direct relationship while a negative coefficient indicates an inverse
relationship. The coefficient of the intercept, on the other hand, indicates the average price given
that all the other variables are zero. Therefore the regression model for used car price determination

USED CAR PROJECT

7

is y = 12,192 – 292.91x1 - 0.01x2 + 16.11x3 ; given x1 represent age, x2 represent mileage and x3
represent fuel.
In conclusion, we can say that the older a car is, the cheaper it is, and the same applies to
mileage covered. However, a car with higher fuel consumption will definitely cost more. It is also
prudent to conclude that the regression model established indicates a very strong relationship as
indicated by an adjusted R-squared of 93.59%. However, this value is not 100% meaning there are
still unexplained 6% determinants of the used car price. One of such factor would the car brand.
Different new cars have different prices based on their brands. This factor does not change just
because the car is second hand. And therefore brand is a significant determinant of a used car price.

USED CAR PROJECT

8
References

Carlberg, C. G. (2014). Statistical Analysis: Microsoft Excel 2013. INpolis, IN: Que.
Cowan, G. (2004). Statistical data analysis. Oxford: Clarendon Press.
McNeill, P., & Chapman, S. (2005). Research methods. London: Routledge.
Wang, G. C., & Jain, C. L. (2003). Regression analysis: modeling & forecasting. Flushing,
NY: Graceway Pub.


Used Car Project
Thesis statement: This report presents a discussion of the most significant factors based on
statistical analysis.
I.
II.
III.

Report on Determinants of Used Car Prices
Descriptive Data
Regression Analysis


Car
Car-01
Car-02
Car-03
Car-04
Car-05
Car-06
Car-07
Car-08
Car-09
Car-10
Car-11
Car-12
Car-13
Car-14
Car-15
Car-16
Car-17
Car-18
Car-19
Car-20
Car-21
Car-22
Car-23
Car-24
Car-25
Car-26
Car-27
Car-28
Car-29
Car-30
Car-31
Car-32
Car-33
Car-34
Car-35
Car-36
Car-37
Car-38
Car-39
Car-40
Car-41
Car-42
Car-43

Year Age Price($) Mileage Power (HP) Fuel (MPG)
2010
2 13400
21000
140
15
2009
3 11400
33000
160
21
2008
4 10600
54000
210
36
2000 12
7600 123000
140
15
1997 15
6000 160000
220
42
1998 14
7000 161000
150
18
2006
6
9700
69000
170
24
2009
3 11600
30000
160
21
2011
1 12000
17000
160
21
2002 10
8000 108000
160
21
2000 12
7400 123000
200
33
2005
7 10500
74000
150
15
2008
4
9700
51000
150
18
2009
3 11300
45000
180
27
1997 15
6400 158000
210
36
2008
4 10600
48000
160
21
2010
2 11400
22000
170
24
1999 13
6800 146000
220
42
2007
5 10900
53000
200
33
1999 13
7400 142000
150
15
2005
7 10300
81000
210
36
2008
4 11700
48000
170
24
2007
5
9600
66000
190
30
2000 12
8000 125000
160
21
2000 12
7600 127000
130
12
2002 10
9000 109000
150
15
2010
2 11000
20000
160
21
2009
3 11000
36000
130
12
2004
8
9800
81000
130
12
2006
6 10700
61000
210
36
1997 15
5600 165000
130
12
2002 10
8600 112000
210
36
2011
1 11800
15000
150
18
2005
7 10600
72000
180
27
1997 15
7300 167000
180
27
1998 14
7000 149000
210
36
1999 13
8000 140000
180
27
2007
5 11200
51000
200
33
2010
2 11700
30000
180
27
2007
5 10600
52000
190
30
1996 16
6500 179000
150
18
2002 10
8600 111000
180
27
2005
7
8600
78000
130
12

Region of origin Single owner
USA
Yes
USA
Yes
Foreign
Yes
USA
Yes
Foreign
Yes
Foreign
Yes
Foreign
Yes
USA
Yes
USA
Yes
USA
Yes
USA
Yes
USA
Yes
USA
Yes
Foreign
Yes
Foreign
Yes
Foreign
Yes
USA
Yes
USA
Yes
USA
Yes
USA
Yes
USA
Yes
USA
No
Foreign
No
Foreign
No
Foreign
No
Foreign
No
USA
No
USA
No
USA
No
USA
No
USA
No
USA
No
Foreign
No
Foreign
Yes
Foreign
Yes
Foreign
Yes
Foreign
Yes
USA
Yes
USA
Yes
USA
Yes
USA
Yes
USA
Yes
USA
Yes

Car-44
Car-45
Car-46
Car-47
Car-48
Car-49
Car-50
Car-51
Car-52
Car-53
Car-54
Car-55
Car-56
Car-57
Car-58
Car-59
Car-60
Car-61
Car-62
Car-63
Car-64
Car-65
Car-66
Car-67
Car-68
Car-69
Car-70
Car-71
Car-72
Car-73
Car-74
Car-75
Car-76
Car-77
Car-78
Car-79
Car-80
Car-81
Car-82
Car-83
Car-84
Car-85
Car-86
Car-87

2001
2000
2001
2000
2009
2010
2010
1998
2005
2008
1996
2003
2006
1996
2000
2005
2005
2008
2008
1996
2003
2001
1998
1998
1996
2010
2006
2006
2005
2009
1998
1998
1996
2007
1996
2002
2007
1996
2000
1999
2009
2000
2003
2005

11
12
11
12
3
2
2
14
7
4
16
9
6
16
12
7
7
4
4
16
9
11
14
14
16
2
6
6
7
3
14
14
16
5
16
10
5
16
12
13
3
12
9
7

7600
7900
8400
7800
11300
11800
12000
6900
9000
11200
6700
8200
10700
6100
7000
9000
10000
10600
11700
6500
9500
8200
6400
6600
6000
12100
10300
10400
9300
10700
7200
5800
5800
10400
6100
9000
11400
5900
6300
6600
11900
7200
9700
9300

114000
125000
123000
138000
35000
24000
26000
144000
80000
38000
175000
91000
75000
178000
130000
84000
77000
43000
40000
166000
98000
123000
155000
154000
180000
21000
65000
72000
74000
39000
161000
148000
180000
55000
180000
105000
64000
175000
127000
135000
27000
132000
101000
86000

150
130
150
190
220
170
130
150
190
210
130
170
210
190
150
210
150
140
210
220
130
190
180
170
130
180
180
190
170
220
180
140
200
220
180
150
220
210
130
150
200
180
140
170

15
12
18
30
39
24
12
18
30
36
12
24
36
30
18
36
18
15
36
42
12
30
27
24
12
27
27
30
24
39
27
15
33
42
27
15
42
36
12
15
33
27
15
24

USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
Foreign
Foreign
Foreign
Foreign
Foreign
Foreign
Foreign
Foreign
Foreign
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
Foreign
Foreign
Foreign
Foreign
Foreign
USA
USA
USA
USA
USA

Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
No
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
No
No
No
No
No

Car-88
Car-89
Car-90
Car-91
Car-92
Car-93
Car-94
Car-95
Car-96
Car-97
Car-98
Car-99
Car-100
Car-101
Car-102
Car-103
Car-104
Car-105
Car-106
Car-107
Car-108
Car-109
Car-110
Car-111
Car-112
Car-113
Car-114
Car-115
Car-116
Car-117
Car-118
Car-119
Car-120
Car-121
Car-122
Car-123
Car-124
Car-125
Car-126
Car-127
Car-128
Car-129
Car-130
Car-131

2010
2000
2009
2001
1997
2008
2011
2006
1998
2006
2000
2006
2004
2007
2005
2004
1996
1997
2001
2004
1999
2008
2006
1997
1999
2010
1997
2005
2004
2009
2009
2006
2004
2009
2006
2009
2011
2000
2011
2008
2000
2005
2006
2000

2
12
3
11
15
4
1
6
14
6
12
6
8
5
7
8
16
15
11
8
13
4
6
15
13
2
15
7
8
3
3
6
8
3
6
3
1
12
1
4
12
7
6
12

11800
7200
11600
7200
6200
11200
13300
11000
7100
10800
7300
9300
9000
10800
10300
8900
5300
5400
7800
9100
6500
11000
9500
6200
7800
12100
6800
10100
9900
12100
11300
10200
8800
10500
10000
12400
12800
7600
11900
10300
7900
9600
10900
8200

31000
126000
43000
127000
162000
50000
6000
68000
144000
74000
126000
77000
95000
55000
86000
94000
179000
170000
112000
92000
145000
55000
77000
171000
138000
34000
160000
70000
86000
34000
32000
63000
87000
30000
62000
41000
20000
135000
8000
45000
140000
80000
64000
131000

220
130
150
150
130
160
160
190
130
180
190
210
130
160
220
130
220
190
190
150
220
140
160
180
210
200
150
190
180
220
220
210
210
180
180
190
210
130
180
130
210
130
220
220

42
12
18
15
12
21
21
30
12
27
30
36
12
21
42
12
39
30
30
18
42
15
21
27
36
33
15
30
27
42
39
36
36
27
27
30
36
12
27
12
36
12
39
42

USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
Foreign
Foreign
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
Foreign
Foreign
Foreign
Foreign
Foreign
Foreign
Foreign
Foreign
Foreign

No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
No
No
No
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes

Car-132
Car-133
Car-134
Car-135
Car-136
Car-137
Car-138
Car-139
Car-140
Car-141
Car-142
Car-143
Car-144
Car-145
Car-146
Car-147
Car-148
Car-149
Car-150
Car-151
Car-152
Car-153
Car-154
Car-155
Car-156
Car-157
Car-158
Car-159
Car-160
Car-161
Car-162
Car-163
Car-164
Car-165
Car-166
Car-167
Car-168
Car-169
Car-170
Car-171
Car-172
Car-173
Car-174
Car-175

2002
2002
1999
1999
2009
2001
2007
2003
2008
1997
2010
1996
2010
2002
2011
2011
2003
1998
2006
2003
2001
2000
2004
2006
1996
2009
2002
1996
2003
2011
2011
2008
2000
2007
1999
2003
2005
2002
2011
2006
1999
2001
2003
2011

10
10
13
13
3
11
5
9
4
15
2
16
2
10
1
1
9
14
6
9
11
12
8
6
16
3
10
16
9
1
1
4
12
5
13
9
7
10
1
6
13
11
9
1

9200
7200
7500
6700
11400
7800
10900
9200
10600
6600
11100
6200
11400
8700
12400
12200
8500
6500
10500
9600
8600
7700
8900
9600
6500
10700
8200
6100
8100
11100
11700
11000
6800
10900
7500
9000
9900
8700
12000
9600
7700
7800
10000
11900

119000
103000
140000
140000
28000
126000
52000
94000
40000
162000
27000
170000
20000
106000
5000
8000
109000
147000
59000
96000
113000
125000
97000
59000
167000
38000
119000
171000
100000
14000
11000
44000
134000
48000
134000
91000
82000
116000
6000
64000
148000
130000
93000
17000

210
130
140
210
160
180
130
190
140
210
220
200
180
160
200
220
160
170
180
190
210
160
140
160
180
150
190
190
190
160
190
210
190
210
150
160
210
200
220
160
160
130
190
140

36
12
15
36
21
27
12
30
15
36
42
33
27
21
33
39
21
24
27
30
36
21
15
21
27
15
30
30
30
21
30
36
30
36
18
21
36
33
39
21
21
12
30
15

Foreign
Foreign
Foreign
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
Foreign
Foreign
Foreign
Foreign
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA

Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
No
No
No
No
No
No
No
No
No
No
No

Car-176
Car-177
Car-178
Car-179
Car-180
Car-181
Car-182
Car-183
Car-184
Car-185
Car-186
Car-187
Car-188
Car-189
Car-190
Car-191
Car-192
Car-193
Car-194
Car-195
Car-196
Car-197
Car-198
Car-199
Car-200
Car-201
Car-202
Car-203
Car-204
Car-205
Car-206
Car-207
Car-208
Car-209
...


Anonymous
I was stuck on this subject and a friend recommended Studypool. I'm so glad I checked it out!

Studypool
4.7
Indeed
4.5
Sitejabber
4.4

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