• Join over 1.2 million students every month
  • Accelerate your learning by 29%
  • Unlimited access from just £6.99 per month
Page
  1. 1
    1
  2. 2
    2
  3. 3
    3
  4. 4
    4
  5. 5
    5
  6. 6
    6
  7. 7
    7
  8. 8
    8
  9. 9
    9
  10. 10
    10
  11. 11
    11
  12. 12
    12
  13. 13
    13
  14. 14
    14
  15. 15
    15
  16. 16
    16
  17. 17
    17
  18. 18
    18
  19. 19
    19
  20. 20
    20
  • Level: GCSE
  • Subject: Maths
  • Word count: 1547

Investigation on Attendence and Grade Mayfield High

Extracts from this document...

Introduction

PLAN

In my investigation I will try to find a relationship between Attendence (%) and GCSE maths (%) of from a sample of 200 students. I will be using a set of secondary data to pick my sample of students.

To start my investigation by picking 25 random students from the sample, I will do this by using a calculator.

SHIFT + RAN# =

However I have found that the method of random sampling is not accurate as the calculator was giving me larger numbers than the sample size. Also I have found that random sampling does not give me an even spread of data, therefore my sample of data will be inaccurate.

Futhermore I have chose to use a more systamatic approach. Therefore I will get a sample with an even spread of data which will be spead out over the sample rather then clustered.

I have chosen to systamatically pick a sample of 25 by picking every 8th student from the data.

200/8 = 25

After choosing my sample of 25 I will go on to organise my data by putting my data into a tally. Once I have done this I will show my data onto a bar graph comparing the Attendence (%) and GCSE maths (%)

...read more.

Middle

image25.png

After observing my data for my mixed sample, I have come up with a hypothesis.

My hypothesis is “the higher your attendence (%) the better GCSE score (%)”.

This shall be my general hypothesis.

The investigation shall be extended to prove my hypothesis.

image26.png

I have put my data into a scatter graph.

Scatter diagrams shows the relationships between attendence (%) and

GCSE score  (%)”.

From looking at the scatter graph I can see a direct link between the two variables. The higher the students attendence (%) is, the better GCSE score (%) they have.

The investigation shall be extended to prove my hypothesis. I have chosen another two sets of data for Males and Females.

I have chosen to systamatically pick a sample of 25 by picking every 8th student from the data.

200/8 = 25

I have chosen a sample of 25 Males and 25 Femlaes using systamatic sampling. I have chosen every 8th male and every 8th Female.

Attendence (%)

Sex

Maths (%)

85.4

M

49

70.7

M

21.9

75.7

M

37.3

83.7

M

50

73.7

M

58.3

88.6

M

46.9

87.4

M

55.4

81.8

M

38.6

82

M

47.1

82.1

M

57.9

96.3

M

72.1

91.2

M

58.1

76.2

M

26.5

94.1

M

52

76.5

M

45

75.6

M

55.2

96.9

M

41.9

81.1

M

58.9

74.1

M

52

89.9

M

58.5

80.2

M

34.9

60. 8

M

27.1

86

M

52.7

82.4

M

36.9

79.1

M

66.2

Attendence (%)

Sex

Maths (%)

62.8

F

29.2

58.8

F

15.6

83.4

F

85

72.6

F

57.2

89.5

F

84.7

87

F

79

77.6

F

62.1

82.8

F

70.3

83.5

F

80.1

82

F

80.2

90

F

83.2

99.1

F

98.5

58.2

F

10.2

73.1

F

56.8

86.3

F

82.3

78.4

F

57.7

96.6

F

100

75

F

60.8

76.5

F

51.9

93.2

F

95.3

86.2

F

73.8

85.4

F

73.9

61.7

F

26.6

96

F

99.1

61.1

F

26.2

Attendence (%)

Tally

Frequency

60>Att<70

1

70>Att<80

8

80>Att<90

12

90>Att<100

4

...read more.

Conclusion

Attendence (%)

image03.png

          50>Mth<60

Tally

Frequency

2

60>Att<70

3

70>Att<80

6

80>Att<90

9

90>Att<100

5

Tally chart for Female data- Attendence (%)

image02.pngimage04.png

I have found there only 2 female students who has Attendence (%) between 50>Mth<60.

The majoraty of female students have a Attendence (%) beween 80>Mth<90.

Tally chart for Male data GCSE maths (%)

GCSE maths (%)

image05.png

10>Mth<20

Tally

Frequency

2

20>Mth<30

3

30>Mth<40

0

40>Mth<50

0

50>Mth<60

4

60>Mth<70

2

70>Mth<80

4

image06.pngimage07.pngimage08.png

image10.pngimage07.pngimage09.png

image12.pngimage11.png

image13.png

image15.pngimage14.pngimage27.png

Attendence (%)

MEAN

MODE

MEDIAN

RANGE

BOYS

GIRLS

image16.pngimage28.png

GCSE Maths (%)

MEAN

MODE

MEDIAN

RANGE

BOYS

GIRLS

image24.png

image29.png

image30.png

image21.png

image22.pngimage17.png

image18.png

image23.png

Conclusion

After carrying out this investigation I have proved my “general hypothesis” to be correct. I have concluded that as the attendence of a pupil increases, the chance that they will get a higher GCSE score wil as increase.  

Evaluation

After carrying out this investigation I have found that I could have improved the accuracy of my data by using primary data. I would use primary data because it is first hand therefore more accurate and it will be to date. The data I used was secondary data this makes it innacurate. Also I could have compared attendence with the final GCSE score of students. Also the sample size diidnt reflect the data, as it was too small. But if the sample that was used were bigger it would have made the investigation too complecated.

...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.

Found what you're looking for?

  • Start learning 29% faster today
  • 150,000+ documents available
  • Just £6.99 a month

Not the one? Search for your essay title...
  • Join over 1.2 million students every month
  • Accelerate your learning by 29%
  • Unlimited access from just £6.99 per month

See related essaysSee related essays

Related GCSE Height and Weight of Pupils and other Mayfield High School investigations essays

  1. Is there a link

    With the xaxis as Maths and the y-axis as Science, I produced the scatter diagram inserted over the page. Studying the scatter diagram, it is clear that there is a link between the Key Stage 2 results for Maths and Science; students who scored high in Maths were more than likely to have scored high in Science.

  2. Trolley Investigation

    For each height the time interval for the trolley to pass through the light gate will be measured 3 times. This will then be repeated for all of the different heights. Analysis As the height of the ramp increased, so did the velocity.

  1. My investigation is to explore the average student.

    Male/Female F F F F F F F F F Height (cm) 171 163 169 160 175 159 179 170 165 Weight (kg) 63 58 65 57 68 60 69 61 58 Left/Right R R R R L R R R R Shoe size 8 6 7 5 9 6

  2. Maths Data Handling

    This suggests that there is a better correlation between height and weight when girls and boys are considered separately. > The scatter graphs can be used to give reasonable estimates of height and weight. This can be shown either by reading from the graph or by equations of lines of best fit.

  1. Mayfield High School Project

    Although when looking at the weight increases, it appears there is a slightly more even increase however the biggest jump is 7kg from year 9-10. The female pupils results generally appears to increase as their age increases, although there is one fault in the weight section.

  2. Mayfield igh Investigation

    168 31 51 162 35 30 137 36 48 160 42 44 152 45 45 174 49 39 160 57 38 163 59 60 170 65 47 168 67 38 156 71 50 155 75 66 160 77 45 159 80 48 152 81 42 153 84 50 169 Year 11 Boys Sample Number Weight(kg)

  1. Introduction to arodynamics - Investigation into the design features of aircraft.

    These strakes, in conjunction with the upper surface of the engine air intakes will induce a vortex which will maintain lift to very high angles of attack. Figure 9. Lift gained due to strakes b. Intakes. As previously mentioned one important consideration in the design of the F-15 is to operate at high AoA.

  2. Conduct an investigation comparing height and weight from pupils in Mayfield School.

    So I can estimate that 18 out of 25 or 72% of boys will be between 140 - 160cm tall. So if I were to select a boy at random from the school, my data suggests that the probability of him having a height between 140 - 160cm is 0.72.

  • Over 160,000 pieces
    of student written work
  • Annotated by
    experienced teachers
  • Ideas and feedback to
    improve your own work