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  • Level: GCSE
  • Subject: Maths
  • Word count: 2089

HEFP STATISTICS ASSIGNMENT REPORT

Extracts from this document...

Introduction

HEFP STATISTICS ASSIGNMENT REPORT

Data Collection: We are asked to find the relationship between prices of  ‘51 registered’ cars and variables such as their current new price, mileage and weight by using the regression analysis. To collect full information of these registered cars, we can access to the websites like: http://www.exchangeandmart.co.ukHowever, in this easy, we use the data, which are provided with the assignment by our teachers.

By the sources, 100 cars, which manufacturers include Toyota, Honda, Nissan, Suzuki, are obtained to be sampled from. These Japanese cars can be divided into three groups according to different engine size, which are small engine size, medium engine size and large engine size. The cars’ engines size under or equal to 1.5 liters are considered as small engine cars. Group of medium engine cars are the cars’ engine size between 1.6 to 2.4 liters. Large engine cars are cars’ engine size equal or bigger than 2.5 liters.

The samples are likely to be representative because the method of simple random sampling will be used. The data of cars is wide range, so we use calculation to choose the samples randomly. The processes of sampling are divided into three procedures.

...read more.

Middle

2

23000

£14,695

£17,008

147

28

Toyota

Pervia 2.4 CDX 5-dr

2.4

25963

£19,950

£22,995

154

29

Nissan

Terrano TD SE 5-dr 4*5

2.7

26572

£15,499

£21,595

123

30

Honda

NSX 3.2 V6 VTEC Coupe

3.2

5600

£55,000

£60,013

276

Preliminary Analysis:

1. Mileage and asking price

image00.png

According to the 30 data we selected, the graph above is produced by excel. As we can see from the graph above, the scatter plots indicates the general impression of the trend is positive. Although the graph is not strongly correlating due to limited samples, to some extent, it is suggested that mileage do influence the asking price of the cars. The formula of correlation should be used to prove whether the impression is right or wrong.

X (Mileage)

Y (Asking Price)

X^2

Y^2

X*Y

1

12480

6,995

155750400

48930025

87297600

2

14283

17,900

204004089

320410000

255665700

3

15038

6,495

226141444

42185025

97671810

4

5000

7,995

25000000

63920025

39975000

5

11840

8,960

140185600

80281600

106086400

6

1344

7,995

1806336

63920025

10745280

7

15600

6900

243360000

47610000

107640000

8

16000

9,995

256000000

99900025

159920000

9

22000

7,495

484000000

56175025

164890000

10

26620

7,495

708624400

56175025

199516900

11

9922

9,995

98446084

99900025

99170390

12

15206

8,995

231222436

80910025

136777970

13

25000

11,995

625000000

143880025

299875000

14

12852

9,495

165173904

90155025

122029740

15

3048

8,495

9290304

72165025

25892760

16

9355

16,895

87516025

285441025

158052725

17

11200

8,995

125440000

80910025

100744000

18

15300

15,495

234090000

240095025

237073500

19

16549

8,495

273869401

72165025

140583755

20

17900

9,995

320410000

99900025

178910500

21

22000

15,495

484000000

240095025

340890000

22

24000

14,795

576000000

218892025

355080000

23

26000

10,450

676000000

109202500

271700000

24

9471

10,995

89699841

120890025

104133645

25

15300

15,495

234090000

240095025

237073500

26

20000

14,495

400000000

210105025

289900000

27

23000

14,695

529000000

215943025

337985000

28

25963

19,950

674077369

398002500

517961850

29

26572

15,499

706071184

240219001

411839428

30

5600

55,000

31360000

3025000000

308000000

SUM

474443

383,944

9015628817

7163472176

5903082453

Correlation coefficient=n Σxy-(Σx)(Σy)/√(n Σx^2-( Σx)^2)(n Σy^2-( Σy)^2)=0.091652

To find the relationship between mileage and price, we should judge whether there is correlation or not. The coefficient of correlation should be compared with critical point. The critical point of 30 data is 0.3061 and obviously, 0.091652 is smaller than 0.3061. Therefore, no strong correlation is found between mileage and price. The correlation between mileage and price is weak probably due to some other factors which affect the asking price.

2. New price and Power

...read more.

Conclusion

Secondly, some significant correlation can be found between the current new prices and maximum powers of cars. For the relationship between current new price and maximum power, my investigation showed that there is a strong correlation. As a result, maximum power is an important determinant factor which influences the current new price. The stronger the maximum power, the higher the new price of the cars. However, due to the limitation of the samples and original data, the result cannot be to be representative. And there are also other factors are able to influence the price of cars, such as the colours, design, brand, taxation, fuel saving, and different agencies.

In spite of the limitations, we can still examine the general trend and predict the price of cars. Regression analysis might help car dealers to set the price and it might let the consumers gain some knowledge of price depreciation.

...read more.

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