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  • Level: GCSE
  • Subject: Maths
  • Word count: 2657

What factors affect the prices of used cars?

Extracts from this document...

Introduction

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AIM

To investigate the factors that affect the price of second hand cars and the extent to which they do, using information made available on a database about various makes of used cars.

HYPOTHESIS

I predict the following factors will affect the price of second-hand cars as explained below:

Make

 I think that the make of a car affects its second hand value because different companies make different cars. These companies make cars that differ in quality, style, prestige, etc, to other manufacturers, which obviously affects their price. It is this value that depreciates a certain percent every year according to the cars desirability and how well the car has been made. For example the second hand price of a BMW is unlikely to be the same as that of a Fiat.

Age

 As I have mentioned before, every year a car loses a certain percentage of its value. The amount a car depreciates every year depends upon the make of the car. The older the car is, the more it has depreciated and the cheaper it is (and vice versa). Therefore, the age of the car affects its second hand value because the older a car gets, the cheaper it gets as opposed to relatively newer cars.

Colour

Everybody wants the car that they are going to spend money on to be the colour that they want. There are some colours that most people would like or wouldn’t mind (e.g. silver)

...read more.

Middle

47

Vauxhall

10

2900

6

Blue

58000

48

Hyundai

6

2800

6

White

49000

49

Daewoo

11

6895

4

Black

14730

50

Daewoo

4

4395

3

Blue

32400

51

Volkswagen

7

3595

6

Red

58000

52

Ford

5

4295

3

White

29000

53

Ford

9

4700

5

Red

34000

54

Bentley

20

37995

8

Red

55000

55

Fiat

3

4500

3

White

13000

56

Lexus

18

6250

7

Blue

57

Ford

7

3200

4

Aubergine

27000

58

Nissan

5

4300

4

Black

17000

59

Rover

14

2975

5

Blue

96000

60

Rover

11

3400

5

Blue

66000

61

Fiat

5

6795

1

Red

3000

62

Peugeot

10

5795

3

Blue

53000

63

Volkswagen

16

6995

5

Black

35000

64

Ford

6

8800

2

Black

7200

65

Ford

9

8250

3

Silver

34000

66

Peugeot

4

7500

1

Silver

18000

67

Peugeot

12

7500

1

Silver

17500

68

Honda

9

7995

1

Green

9500

69

Rover

9

14999

1

Grey

2000

70

Fiat

5

4995

2

Green

18500

71

Land Rover

13

13995

1

Blue

40500

72

Mercedes

12

17500

2

Silver

22000

73

Porsche

20

19495

6

Silver

46000

74

Volkswagen

11

13500

1

Silver

6500

75

Rover

14

2975

6

Blue

96000

76

Suzuki

9

2995

8

Red

50000

77

Mercedes

7

11750

2

Silver

17000

78

Audi

13

3995

7

Purple

103000

79

Volkswagen

5

7550

1

Blue

5000

80

Ford

10

3495

7

Red

43000

81

Ford

11

7995

4

Cuirass

30000

82

Mazda

8

2495

7

Green

50000

83

Rover

10

3685

6

Blue

64000

84

Vauxhall

3

4976

4

Red

21000

85

Vauxhall

3

3495

6

Green

55000

86

Ford

4

1664

10

Red

37000

87

Nissan

10

2574

9

Grey

49000

88

Citroen

9

2450

8

Red

49000

89

Peugeot

5

2497

8

Red

71000

90

Peugeot

5

3995

6

White

71000

91

Fiat

3

3769

4

...read more.

Conclusion

Conclusion and Evaluation

In conclusion, three of the five factors that I chose turned out to be correct while two turned out to be incorrect according to the results obtained in this investigation. The correct ones were the make, age and mileage while the insurance group and colour were incorrect.

It must be taken into consideration that all the factors are interlinked and therefore could have caused anomalous results or discrepancies.

None of the graphs showed strong correlations showing that there are many factors that affect the price depreciation and they are all interlinked and are made obvious on the graphs.  

I could possibly have obtained better results if I had tested more, or even all the cars. This would give me accurate results but would be time consuming. Also, on the box plots I should have used a wider variety/range of cars to show me the contrasts and my results better.

As there are so many factors that do affect the prices of used cars, in future experiments I could investigate using more factors such as the price when new and the amount of owners the cars had.

I could have extended my investigation by using standard deviation to estimate the spread of my data before plotting the graphs. This would have given me an idea on whether my predictions were valid or not.

Tehsin Haji

...read more.

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