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  • Level: GCSE
  • Subject: Maths
  • Word count: 2203

Data Handling

Extracts from this document...

Introduction

Helen Steers        11Y3                Mr. Holt

Data Handling Coursework.

There are many different types of data that can be gained from groups of people, in which can be explored and experimented with. Such data could include:

Favourite sport

Height

KS2 maths score

Transport to school

Favourite television programme

Eye colour

Year group

Left/ right handed

IQ level

KS2 English score

Favourite colour

Hair colour

Number of siblings

Weight

Most of this data can be categorised into two groups’ continuous data and discreet data.

Continuous data: This can take any value. For example foot length is a type of continuous data. It can not be measured exactly. The accuracy of measurement depends on the accuracy of the measuring device.

Discreet data: This can only take particular values. For example shoe sizes: 6, 6½, 7, 7½, 8. These values are discrete (meaning separate). There are values between them. Discrete data has an exact value.

Certain data have been rejected as I have chosen to use weight and height to investigate. The following are the reasons why I have rejected these other types of data:

  • Favourite Sport. This data has been rejected as the possible answers would be far too      

varied.

  • Ks2 maths and English scores. This data has been rejected as a hypothesis for this

type of data would not necessarily be true.

  • Transport to school. This data has been rejected as it could not have a logical

hypothesis.

  • Favourite television programme. This data has been rejected as the answers would

be far too varies

  • Eye colour. This data has been rejected as a hypothesis given would not necessarily

be true for everyone with the same eye colour.

  • Left/right handed. This data has been rejected as it could not have a logical      hypothesis.
  • IQ level. This data has been rejected because a hypothesis will not necessarily be true for every one.
  • Favourite colour. This data has been rejected because it can have no logical hypothesis.
  • Hair colour. This data has been rejected as a hypothesis given would not necessarily

be true for everyone with the same hair colour.

  • Number of siblings. This data has been rejected as a hypothesis given would not necessarily be true fore everyone with the same number of siblings.
...read more.

Middle

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

Height (m)

1.60

1.72

1.73

1.63

1.68

1.61

1.51

1.70

1.63

1.68

1.68

1.58

1.37

1.57

2.00

1.62

1.74

1.60

1.68

1.80

1.70

1.63

1.62

1.62

1.62

1.72

1.57

1.61

1.69

1.80

Weight (Kg)

54

51

50

48

48

54

40

50

45

50

48

54

30

48

86

48

39

48

63

68

56

38

50

54

48

64

54

42

42

62

Scatter Graphs

image00.png

image01.png

Stem and Leaf diagrams

Year 7- Height

1.30

1.40

1.40

1.50

1.50

1.60

1.70

0

2 1 2

7 8 7 6 8

1 3 4 0 4

5 9 8 7 6 5 9 9

5 2 5 3 4 7 3

2

Year 7- Weight

20

30

40

50

60

6 6

5 5 0 2 8 0 1 0 0 4 7 5 0 8 4 0 0

0 0 2 5 2 7 0 1 3

0 0

Year 11-Height

1.30

1.40

1.50

1.60

1.70

1.80

1.90

2.00

7

1 8 7 7

0 3 8 1 3 8 8 2 0 8 3 2 2 2 1 9

2 3 0 4 0 2

0 0

0

Year 11-Weight

30

40

50

60

70

80

 0 9 8

8 8 0 5 8 8 8 8 2 2

4 1 0 4 0 0 4 6 0 4 4

3 8 4 2

6

Year 7 Height- Cumulative Frequency Graph

Height

Frequency

Cumulative Frequency

1.30<h≤ 1.40

1

1.40<h≤ 1.50

9

1.50<h≤ 1.55

14

1.55<h≤ 1.60

22

1.60<h≤ 1.70

29

1.70<h≤ 1.80

30

Year 7 Weight- Cumulative Frequency Graph

Weight

Frequency

Cumulative Frequency

...read more.

Conclusion

How to improve the investigation and the results gained

There are many ways in which this investigation could either be extended or improved. Firstly I limited the amount of data I used. Instead of just using 30 pupils from each year group more pupils’ data could be used, for example 60 pupils’ data could be used instead.

Another way to extend the investigation would be to use more year groups, instead of just two. For example all years, 7, 8,9,10 and 11 could be used to gain more data and possibly better results.

Also different school could be used in the investigation. Maybe two different schools data could be used and then compared to give a completely different result. Or maybe just the same year groups could be used from two different schools and therefore a wider range of data would be provided, resulting again in a different outcome.

Another way to extend on this investigation could be to use pupils’ data from different countries. Two lots of pupils’ data could be used from two different countries and compared or added together to give a wider variety of results.

All of these suggestions would give the new investigation results with very different answers and therefore different hypothesis would be needed to be made.

...read more.

This student written piece of work is one of many that can be found in our GCSE Height and Weight of Pupils and other Mayfield High School investigations section.

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