# Maths Project. Statistical Analysis of GCSE results at my secondary school summer 2010

Extracts from this document...

Introduction

Leatitia Teboh

Maths Studies Group

Statistical Analysis of GCSE results at my secondary school summer 2010

Introduction

For my maths project, I requested for the summer 2010 GCSE Exam results from St Bede’s secondary schoolExam moderator; so as to analyse it. Having received the data, I made the names of the students anonymous, to keep their information private. I kept the data in alphabetical order so that my hypothesis would make sense. I identified the gender for the 186 students that wrote the exam; which took a lot of time to get the data ready and to make it private.

I had to search on the internet for the equivalent GCSE grade points so that I could change the grades to points so as to have a good set of data for my analysis. My hypothesis for my maths project base on the GCSE result summer 2010 is the lower down you are in the alphabetical order of the registration the less you do well in the exams and by that having low GCSE results at the end, while the higher up you are in the register the better you do and having a good GCSE result at the end.

So by my hypothesis the graphs that I am going to produce base on my data results should have a negative trend (line of best fit) and for it to have a negative trend showing my hypothesis, what I did was numbered the students starting from the last student on the alphabetical order in the register numbering him/her number 1 and numbering the first student on the alphabetical order register number 186.

Middle

40

40

f

80

178

Be

10

40

46

m

86

177

Bi

10

40

28

m

68

176

Bi

8

40

40

m

80

175

Bo

8

52

52

m

104

174

Br

10

40

40

m

80

173

Br

12

46

46

f

92

172

Br

8

46

40

m

86

171

Bu

11

40

46

m

86

170

Bu

10

58

52

m

110

169

Bu

10

40

40

f

80

168

Bu

9

46

52

m

98

167

Ca

9

46

46

f

92

166

Ca

10

58

58

f

116

165

Ca

10

52

58

m

110

164

Ca

6.5

28

28

m

56

163

Ch

7.5

28

34

m

62

162

Ch

8

40

40

f

80

161

Cl

10

46

46

f

92

160

Cl

9

40

52

m

92

159

Cl

11

52

46

f

98

158

Co

10

40

28

f

68

157

Co

8

40

40

m

80

156

Co

6.5

28

28

m

56

155

Co

10

40

22

f

62

154

Co

9

52

52

f

104

153

Co

9

46

46

f

92

152

Co

10

40

34

m

74

151

Cr

9

46

40

f

86

150

Cr

10

40

40

f

80

149

Cu

10

34

28

m

62

148

Da

7.5

34

28

m

62

147

Da

8

40

46

f

86

146

Da

8.5

34

28

m

62

145

De

9

58

52

f

110

144

Do

8.5

34

28

m

62

143

Ed

10

40

40

f

80

142

Eg

9

46

40

f

86

141

El

9

46

34

m

80

140

Ev

9

46

34

f

80

139

Fa

10

46

52

m

98

138

Fr

8

58

52

m

110

137

Fa

9

52

40

f

92

136

Fe

10

46

40

f

86

135

Fi

7.5

34

28

m

62

134

Fl

10

46

52

f

98

133

Fo

8

34

40

f

74

132

Fo

8.5

28

28

m

56

131

Fo

12

40

40

f

80

130

Ga

11

52

46

f

98

129

Ge

9

46

52

f

98

128

Ge

9

46

52

m

98

127

Go

10

58

46

m

104

126

Go

12

46

28

f

74

125

Gr

8.5

40

34

m

74

124

Gr

10

40

34

m

74

123

Gr

9

40

34

f

74

122

Gu

10

52

52

f

104

121

Ha

10

46

40

m

86

120

Ha

10

52

40

f

92

119

He

10

40

40

m

80

118

Hi

9

46

52

m

98

117

Ho

10

40

34

m

74

116

Hu

7.5

34

28

m

62

115

Hu

9

52

52

m

104

114

Iw

11

46

40

f

86

113

Ja

10

46

46

f

92

112

Ja

9

40

46

f

86

111

Ja

9

46

40

m

86

110

Ke

11

40

28

m

68

109

Ki

8

40

46

m

86

108

La

8

34

22

f

56

107

La

8

58

52

f

110

106

La

11

46

34

f

80

105

Le

12

52

46

f

98

104

Le

9

40

40

f

80

103

Le

9

40

46

m

86

102

Le

10

34

28

f

62

101

Li

8

28

22

m

50

100

Lo

9

34

28

m

62

99

Lo

10

46

34

f

80

98

Ma

9

52

58

m

110

97

Ma

10

40

34

f

74

96

Ma

9

40

34

m

74

95

Ma

12

58

52

f

110

94

McC

8

34

40

m

74

93

McC

9

40

46

m

86

92

McG

10

34

28

m

62

91

McM

9

34

40

m

74

90

McMi

9

46

46

f

92

89

Mi

10

46

52

f

98

88

Mi

11

40

40

m

80

87

Mi

10

34

28

m

62

86

Mi

8.5

28

22

f

50

85

Mi

8

34

28

m

62

84

Mo

10

46

40

f

86

83

Mo

10

46

46

f

92

82

Mo

9

52

58

f

110

81

Mo

9

46

52

m

98

80

Mo

9

34

22

m

56

79

Mo

9

40

46

m

86

78

Mo

10

52

52

m

104

77

Mo

9

52

52

f

104

76

Na

9

40

40

m

80

75

Na

10

40

34

m

74

74

Ne

9

46

52

m

98

73

Ne

10

40

40

m

80

72

Ng

11

46

46

m

92

71

Nu

8.5

34

40

m

74

70

O'D

10

40

40

m

80

69

O'D

8

28

46

m

74

68

Ol

11

34

34

m

68

67

Or

9

46

40

f

86

66

Pa

9

40

52

m

92

65

Ph

10

40

40

m

80

64

Po

10

28

34

m

62

63

Po

11

46

46

m

92

62

Re

8

40

40

m

80

61

Re

9

40

40

f

80

60

Ri

11

52

46

m

98

59

Ro

9

40

46

m

86

58

Ro

9

40

46

m

86

57

Ro

9

52

40

f

92

56

Ro

10

52

40

m

92

55

Ro

9

58

52

m

110

54

Ru

7

34

46

m

80

53

Ru

11

46

40

m

86

52

Sa

10

46

46

m

92

51

Sa

7

40

34

f

74

50

Sc

10

46

46

f

92

49

Sh

12

46

40

f

86

48

Si

10

34

34

f

68

47

So

10

34

28

f

62

46

Conclusion

Median | 40 |

Standard deviation is a measure of how widely values are dispersed from the average value (which is the mean). To calculate the standard deviation my data I used the Microsoft formula function which was ‘=STDEVA(C10:AF195)’ which as you can see below my standard deviation for my data is 9.5003691.

Standard Deviation | 9.5003691 |

Conclusion

Having analyzed my data base on the 2010 GCSE results from my secondary school, I have disprove my hypothesis because having looked at the graphs the mean, the mode, the median and the correlation from my data, it shows that it did not matter where a student was placed on the register alphabetically because my hypothesis where meant to be showing a negative correlation but instead it showed a positive correlation and some of the graphs did not show any correlation at all. So my hypothesis was wrong because student being at the bottom of the alphabetic register did much well as the students with their names being at the top of the alphabetical rooter. Even though I tried to prove the point that students might do very well in math’s and be really bad in Religious studies did not also work because the graph turned up to be a positive correlation as well disproving me that in my secondary school the GCSE result 2010, the students where multi-covered in all the areas of the department in school leading them to do well in all their subjects so as to balance out and come out with good GCSE results in all their subjects.

This student written piece of work is one of many that can be found in our International Baccalaureate Maths section.

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