Determinates Of Car Price

Determinates Of Car Price

CONTENTS:

Introduction

PART ONE:

I. TYPE OF CARS AND THEIR PRICES

II. MILES PER GALLON AND CAR TYPE

III. CAR PRICE AND HORSE POWER

PART TWO:

I. MILES PER GALLON VERSUS PRICES

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II. MILES PER GALLON AND THE ENGINE SIZE

Conclusion

References

APPENDIXES:

Introduction:

The price of cars will depend on the type, horse power and other factors, the type of cars can be grouped into compact, small, midsize, large, sporty and van. However depending on the manufacturer the price varies, this paper focuses on the type of cars and how the price varies and also the variables that determine the price of cars.

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In this paper we will analyze the various factors that affect the cost of cars, the final price of the car will depend on the type of car, from the analysis cars are divided into various categories and their basic price determined, hypothesis tests are also carried out to determine the validity of the conclusion that some cars are more expensive than others.

The paper also focuses on the various variables that affect the value of miles per gallon of a car, one of the factor analyzed include the engine size whereby it is clear that the larger the size the more the consumption per mile. We also comp[are the miles per gallon and the type of car, in this analysis it is clear that small cars have high value of miles per gallon but their price is still low, this shows that some car types are more economical in terms of consumption and still are sold at very low prices.

Type of cars and price:

From the data available for analysis it was clear that the price of cars depended on the car type, the mean price is high for the mid size cars than any other car, the lowest mean price is that of the small type of cars, the table below summarizes the mean values of price:

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car  type

mean  basic price

mean  top price

compact

1

15.7

20.7

small

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2

8.4

11.9

midsize

3

24.1

30.3

large

4

22.9

25.7

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sporty

5

16.9

22.0

van

6

16.2

22.0

From the above table it is clear that mid size cars are more expensive than any other car with a mean price of 24.1 thousand, the low cost cars are the small cars whose mean price is 8.4. the high price may be as a result of the high demand in the market, The chart below summarizes the mean prices for the different type of cars:

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From the chart above it is evident that the mid size cars have a higher mean price, followed by the large cars, then the sporty cars and the lowest mean price is the small cars. The prices of cars depend on many factors including the demand and supply level and also other factors associated with the car.

We test the hypothesis that the price for medium cars is higher than the price for the small cars, this will require us to state our null and alternative hypothesis and also find the mean and standard deviation for the two means, the table below summarizes the mean and standard deviation for the two type of cars:

car  type

mean  basic price

standard  deviation

small

2

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8.4

1.493031432

large

4

22.9

6.260714452

The above table summarizes the mean basic price of both large and small cars, it also conatins the standard deviation of the basic price mean, the above information will help us to undertake a hypothesis test on the means.

Our null hypothesis is as follows:

H0:S=L

Alternative hypothesis is as follows:

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Ha: L> S

Where S is the mean basic price for small cars and L is the mean basic price for the large cars.

L – S

Z =  ___________

[(Lσ12/ n1) + (Sσ22/ n2)] ½

Where σ is the standard deviation

Our Z therefore is equal to 7.573550735, at 98% level of test this value exceeds the critical value and therefore we reject the null hypothesis that S = L, for this reason therefore we conclude that the mean price for large cars is higher than the mean price for the large cars.

Miles per gallon versus type of car:

The MPG of cars will differ with the type of car, we expect that small cars will have a large value of mile per gallon than any other car and this depends on the size of the engine and that

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they are economical and also posses low horse power. The following chart summarizes the miles per gallon for the different types of cars.

Small type of cars have a larger mean mile per gallon than any other car, larger cars on the other hand have the lowest mile per gallon, this mean that small cars are more economical than larger cars, the higher the miles per gallon means that the car is efficient and more economical than any other car and in our case the small cars fall under this category.

Car price and horse power:

We hypothesis that the price of cars will depend on the level of horse power, horse power refers to the driving power of a car, for this reason we check the various types of cars and their mean horse power and compare with the price. We expect that the higher the horse power level then the higher is the price per unit for a car. the following table summarizes the mean horse power and the mean basic prices for each car type:

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car  type

mean  basic price

horse  power

compact

1

15.7

131.0

small

2

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8.4

91.0

midsize

3

24.1

173.1

large

4

22.9

179.5

sporty

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5

16.9

160.1

van

6

16.2

149.4

From the above table we summarize the mean price and horse power for the various types of cars, the small cars have low horse power level while large cars have a high horse power level, it is therefore evident that a small car will have a low price due to the low horse power level while the large cars will have a higher price due to the horse power level, the following chart shows a scatter diagram demonstrating the x axis as the horse power level and Y axis as the price:

The above chart shows the excel output of a scatter diagram of horse power versus the price,

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the line shows the trend line that depicts a line of best fit. From the chart it is clear that as the level of horse power increases then the higher is the price, this shows that cars with a higher horse power level will cost more. We can therefore conclude that the price of cars will depend on the horse power whereby the higher the horse power level of a car then the higher is the price.

Miles per gallon versus the price:

We now analyze the relationship between miles per gallon versus the price, in this case we will compare all the cars prices versus the price, for this reason we will use the entire sample to analyze this relationship. It is evident from previous analysis that a high level of miles per gallon will be associated with the small cars that have low cost price, for this reason therefore we expect that the higher the basic price then the lower the miles per gallon, the following chart summarizes the entire sample and shows the relationship between miles per gallon and the basic price:

The above is an excel output showing a scatter diagram portraying the relationship between the price and miles per gallon, the trend lien shows the line of best fit and it clearly shows that the higher the level of miles per gallon then the lower is the price, from the output also we achieve a regression model for the data which states that Y = -0.4X + 29.22. Where Y is the price and X is the miles per gallon, this means that when we increase the miles per gallon by one unit then the level of price declines by 0.4thousand dollars and that if the level of miles per gallon is zero then the price level would be 29.22. For this reason the cars with lower miles per gallon will be highly priced while those with higher miles per gallon then the lower the price.

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The R squared or the correlation of determination for this regression is 0.388 meaning that only 38.8% of deviation in prices is explained by the level of miles per gallon. The correlation coefficient for the data is -0.62288 meaning that there is a strong negative relationship between the two variables, the negative correlation means that as one variable increase then the other variable will be declining.

We now test the statistical significance of the estimated regression, this will involve

The table below summarizes the standard error of our estimated coefficients:

std  error

a

3.521786342

b

0.152766014

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Having determined our standard error we can determine whether they are statistically significant:

The slope b:

Null hypothesis

H0: b = 0

Alternative hypothesis

Ha: b ≠ 0

Z = b/std error

Z = -0.4/0.152766014

Z = -2.618383434

At 95% level of test we conclude that the slope coefficient is statistically significant because the calculated value of Z exceeds the critical value, for this reason therefore we accept the

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alternative hypothesis and state that the slope is statistically significant.

The autonomous value:

The constant a:

Null hypothesis

H0: a = 0

Alternative hypothesis

Ha: a ≠ 0

Z = a/std error

Z = 8.296925811

At 95% level of test we conclude that the constant coefficient is statistically significant because the calculated value of Z exceeds the critical value, for this reason therefore we accept the

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alternative hypothesis and state that the constant is statistically significant.

Miles per gallon and the engine size:

We now analyze the relationship between the engine size and the miles per gallon, we expect that the larger the engine size then the lower the level of miles per gallon per car, this is because we expect that the larger the car the more the consumption level of fuel, the chart below summarizes the entire data:

The above diagram shows the scatter diagram depicting the miles per gallon and the engine size, the diagram shows the trend lien that depict that as the engine size increases then the miles per gallon declines, this is to state that cars with bigger engines are less economical due to the high consumption of fuel.

Regression of the data shows that Y = -3.846X + 32.62 where Y is miles per gallon and X is the engine size, when the engine size increases by one unit according to this estimated model

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then the miles per gallon level decline by 3.846, however if the engine size is zero then the level of miles per gallon will be32.62 according to the model.

The R squared value or the correlation of determination is 0.504 meaning that 50.4% of deviation in the miles per gallon is explained by the engine size, the correlation coefficient r in this case is -0.71meaning that there is a strong but negative correlation between the two variables, negative correlation here means that as one variable increases then the other variable is decreasing.

The standard error for the slope coefficient is 0.399913 while that for the constant a is

10.3516, having calculated our standard error we can test hypothesis on the significance of the coefficients. we stated our model as Y = A + bX where Y is the miles per gallon and X is the engine size we check for the statistical significance of our estimated coefficients as follows using test hypothesis:

Having determined our standard error we can determine whether they are statistically significant:

The slope b:

Null hypothesis

H0: b = 0

Alternative hypothesis

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Ha: b ≠ 0

Z = b/std error

Z = -9.617084576

At 95% level of test we conclude that the slope coefficient is statistically significant because the calculated value of Z exceeds the critical value, for this reason therefore we accept the alternative hypothesis and state that the slope is statistically significant.

The autonomous value:

The constant a:

Null hypothesis

H0: a = 0

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Alternative hypothesis

Ha: a ≠ 0

Z = a/std error

Z = 3.15120306

At 95% level of test we conclude that the constant coefficient is statistically significant because the calculated value of Z exceeds the critical value, for this reason therefore we accept the alternative hypothesis and state that the constant is statistically significant.

Conclusion:

From the above analysis it is clear that the price of cars will depend on the type of car, the types of cars are grouped into categories which include large cars, sporty cars, medium size, compact cars and vans. The lowest mean price is the small cars smaller cars have a lower basic price compared to the medium size cars which have the highest mean basic price. The

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price difference depends on the engine size and other factors.

Our next analysis involved checking the relationship between miles per gallon and the basic price, from this analysis it was evident that Small type of cars have a high mean mile per gallon than any other car, larger cars on the other hand have the lowest mile per gallon, this mean that small cars are more economical than larger cars, the higher the miles per gallon in this analysis showed that a high miles per gallon is a symbol of efficiency and the cost of maintenance.

It was also evident that there was a difference in the horse power and the type of car, the small type of cars had low mean horse power level compared to the larger cars it was therefore evident that small car will have a low price due to the low horse power level while the large cars will have a higher price due to the horse power level.

Regression analysis was also undertaken to determine the relationship between the miles per gallon and the other variables, for the relationship between miles per gallon and the price it was evident that those cars with a high miles per gallon had a low price in the market, the model estimated was stated as Y = -0.4X + 29.22 Where Y was the price and X was the miles per gallon, meaning that increasing the miles per gallon by one unit will reduce the price by 0.4 thousand. Statistical hypothesis testing also showed that the estimated coefficients were statistically significant.

The other regression was undertaken to determine the relationship between the relationship

between the miles per gallon and the engine size, the estimated model showed that Y =

-3.846X + 32.62 where Y was miles per gallon and X was the engine size, this model shows

that when the engine size increases by one unit then the miles per gallon level decline by 3.846, this clearly shows that the bigger the engine then the lower the miles per gallon, from this analysis it was evident that the bigger the engine the higher the consumption and therefore the less efficient the car.

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The above analysis therefore could help in guiding buyers and sellers to the best choice of cars, buyers are aiming at maximizing their utility by reducing the maintenance cost and yet getting the car they desire, for this reason therefore the above analysis would be helpful in further understanding of the products offered in the market and therefore help in making optimal decision.

References:

Burbidge S. (1993) Statistics: An Introduction to Quantitative Research,McGraw Hill, New York

Bridge D. (1994) Statistics: An Introduction to Quantitative Economic Research, Rand McNally publishers, Michigan

Chambers R (2003) Analysis of Survey Data, Wiley publishers, New York

D Amaratunga and et al (2002) Quantitative and qualitative research, McGraw Hill publishers, New York

R. Bogdan and K. Biklen (1992) Qualitative Research: Introduction to Theory and Methods, MIT press, London

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Appendixes:

1=compact

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Manufacturer

Model

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Car  Type

Basic  price

Top  Price

MPGTown

MPGBest

AirBag

Cyl

HP

Length

Engine  size

PassCap

RPM

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Weight

mean

15.7

20.7

22.7

29.9

0.8

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4.1

131.0

182.1

2.3

5.1

5362.5

2918.1

stad  deviation

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5.873155739

7.960946342

1.92245503

2.9410882

0.65510813

0.5

22.77133

3.792537

0.267628

0.442531

461.6998

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216.386

median

14.1

18.5

23.0

30.0

1.0

4.0

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132.0

181.5

2.3

5.0

5450.0

2970.0

mode

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13

18.3

20

31

1

4

110

184

2.2

5

5600

3085

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2 SMALL Model Car Type Basic price Top Price MPGTown MPGBest AirBag Cyl

HP

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Length

Engine  size

PassCap

RPM

Weight

mean

8.4

11.9

29.9

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35.5

0.2

3.9

91.0

167.2

1.6

4.6

5633.3

2312.9

stad  deviation

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1.493031432

2.803297378

6.10971124

5.6090913

0.43643578

0.358569

21.15656

10.15686

0.269214

0.497613

469.3968

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267.304

median

8.2

11.3

29.0

33.0

0.0

4.0

90.0

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172.0

1.6

5.0

5600.0

2345.0

mode

8.4

10

29

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33

0

4

92

172

1.8

5

6000

2295

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3=midsize

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Manufacturer

Model

Car  Type

Basic  price

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Top  Price

MPGTown

MPGBest

AirBag

Cyl

HP

Length

Engine  size

PassCap

RPM

Weight

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mean

24.1

30.3

19.5

26.7

1.1

5.5

173.1

192.5

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3.1

5.1

5336.4

3400.0

stad  deviation

10.15233004

15.08554324

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1.89554045

2.5105837

0.71016125

1.224745

52.49844

6.037401

0.735274

0.560226

596.4542

321.355

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median

23.1

27.4

19.0

26.5

1.0

6.0

169.0

191.5

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3.0

5.0

5300.0

3472.5

mode

14.2

18.4

19

47/76

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26

1

6

110

188

3

5

5200

#N/A

4=large

48/76

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Determinates Of Car Price

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Manufacturer

Model

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Determinates Of Car Price

Car  Type

Basic  price

Top  Price

MPGTown

MPGBest

AirBag

Cyl

HP

Length

Engine  size

PassCap

RPM

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Weight

mean

22.9

25.7

18.4

26.7

1.4

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6.7

179.5

204.8

4.2

6.0

4672.7

3695.5

stad  deviation

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6.260714452

6.668746645

1.50151439

1.2720778

0.50452498

1.00905

21.84199

11.35622

0.793038

0

544.2259

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254.1403

median

19.9

21.9

19.0

26.0

1.0

6.0

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Determinates Of Car Price

170.0

203.0

3.8

6.0

4800.0

3570.0

mode

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#N/A

21.7

19

28

1

6

170

203

3.8

6

4800

3470

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5=sporty

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Manufacturer

Model

Car  Type

Basic  price

Top  Price

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Determinates Of Car Price

MPGTown

MPGBest

AirBag

Cyl

HP

Length

Engine  size

PassCap

RPM

Weight

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mean

16.9

22.0

21.8

28.8

1.0

4.9

160.1

175.2

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2.5

3.7

5392.9

2899.6

stad  deviation

7.895345687

8.573098738

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3.90617994

3.6411869

0.67936622

1.320451

74.40622

10.47472

1.149223

0.726273

574.0735

407.6219

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median

13.7

21.2

22.5

28.5

1.0

4.0

147.5

174.5

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2.3

4.0

5450.0

2857.5

mode

#N/A

#N/A

19

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Determinates Of Car Price

25

1

4

160

179

3.4

4

4600

3240

6=van

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Manufacturer

Model

Car  Type

Basic  price

Top  Price

MPGTown

MPGBest

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Determinates Of Car Price

AirBag

Cyl

HP

Length

Engine  size

PassCap

RPM

Weight

mean

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Determinates Of Car Price

16.2

22.0

17.0

21.9

0.3

5.7

149.4

185.7

3.2

7.1

4744.4

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3830.6

stad  deviation

2.027929979

3.009152705

1.22474487

1.4529663

0.5

0.707107

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19.2426

7.466592

0.634429

0.333333

320.5897

154.0991

median

16.6

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Determinates Of Car Price

21.7

17.0

22.0

0.0

6.0

151.0

187.0

3.0

7.0

4800.0

3735.0

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mode

14.7

#N/A

18

23

0

6

170

194

75/76

Determinates Of Car Price

3

7

4800

3715

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