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The factors that affect used car prices.

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Introduction

The factors that affect used car prices

Planning

In this experiment we are going to be collecting data in such a way so that it can show us which factors affect used car prices the most and also the least. To give us a vague idea of which were most popular amongst the general public each class member did a survey on every member of their household to see which factors of a car affect them most when purchasing such a vehicle. The results of which are shown below.

Owners

Age

Colour

Price

Make

MPG

Air conditioning

Tax

MOT

5

29

3

13

22

9

11

1

1

6

1

7

3

2

5

4

=8

=8

As you can see from the table of results the most popular factor was age, however I believe that some of the data could be bias as the people giving the data may have been in a rush at the time or not have put much effort in.  In this experiment I am going to try and use as many varying data collection methods to try and get the best of the data that I am going to use.

Hypothesis 1

My first hypothesis is that the higher the first hand price is the higher the second hand price will be, I have recognised that this is quite an obvious hypothesis, however looking at this will

...read more.

Middle

Lanos

11225

5999

46.5567929

3

Lower quartile=44

9

Renault

Megane

13175

6999

46.8766603

3

5

Nissan

Micra

7995

3999

49.9812383

3

Median=47

50

Daewoo

Lanos

9525

4395

53.8582677

3

62

Peugot

406LX

13975

5795

58.5330948

3

Upper quartile=53

52

Ford

Escort

12125

4295

64.5773196

3

Highest

Car

Make

Model

Price when

Price

Percentage

Age

Upper and lower quartile

 Number

 New

Second Hand

Depreciation

Boundaries

84

Vauxhall

Corsa

7840

4976

36.5306122

4

Lowest

10

Vauxhall

Tigra

13510

7499

44.4929682

4

91

Fiat

Punto

7518

3769

49.8669859

4

49

Daewoo

Nubira

13850

6895

50.2166065

4

51.5

15

Fiat

Punto

8601

3995

53.5519126

4

4

Vauxhall

Astra

14325

6595

53.9616056

4

81

Ford

Mondeo

17780

7995

55.0337458

4

median=54

57

Ford

Fiesta

8680

3200

63.1336406

4

6

Renault

Megane

13610

4999

63.2696547

4

12

Vauxhall

Vectra

18140

6499

64.1730981

4

64

58

Nissan

Almera

12590

4300

65.8459095

4

8

Rover

623 Gsi

22980

6999

69.5430809

4

Highest

Car

Make

Model

Price when

Price

Percentage

Age

Upper and lower quartile

 number

 New

Second Hand

depreciation

boundaries

92

Volkswagen

Polo

8710

4693

46.119403

5

lowest value

63

Volkswagen

Golf GTi

16139

6995

56.6577855

5

53

Ford

Escort

11800

4700

60.1694915

5

57

100

Vauxhall

Vectra

13435

4995

62.82099

5

11

Fiat

Bravo

10351

3495

66.2351464

5

median=64

96

Ford

Escort

15405

3995

74.0668614

5

60

Rover

620Si

17795

3400

80.8935094

5

75 .5

59

Rover

623GSi

24086

2975

87.6484265

5

highest

Car

Make

Model

Price when

Price

Percentage

Age

Upper and lower quartile

 number

...read more.

Conclusion

Hypothesis 3

For this hypothesis I had to take into consideration everything that I have found out during the experiment so far. I have discovered that all expensive cars have luxury facilities and practical facilities. Whereas cheaper cars only have practical facilities that are a necessities.  With this in mind I thought I would look at a luxury facility, as only an expensive car would have a luxury facility and therefore an expensive car new is an expensive car old as proven by our hypothesis 1.  so with all this in mind I have decided to look at which cars have air conditioning and which don’t.  As not only does this determine whether it’s an expensive car or not, but it also is a commodity that most people would love in their own car and therefore would push the buy every time. What I am going to do is use a cumulative frequency histogram for all the cars with air conditioning and without air conditioning. I will be using a cumulative frequency histogram so that I can determine the upper and lower quartiles and the mean on both.

Conclusion

And to conclude the experiment went very well and all things went according to my hypothesis.  And I feel there is much more that could be elaborated upon to push the experiment even further.

...read more.

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    41000 1.4 47 Vauxhall Astra 13740 2900 6 58000 1.6 48 Hyundai Accent 6899 2800 6 49000 1.3 49 Daewoo Nubira 13850 6895 4 14730 2 50 Daewoo Lanos 9525 4395 3 32400 1.4 51 Volkswagen Golf 12999 3595 6 58000 1.8 52 Ford Escort 12125 4295 3 29000 1.4

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