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I have chosen this particular hypothesis because many students who tend to have a high IQ, have a high KS2 result too. I have also chosen this hypothesis because, many students at my school who have a high IQ tend to do well in their KS2 exams and get a high grade and therefore I would like to find this out for my-self.

The data which I will be using to find out if my hypothesis is right or wrong will be from Mayfield High School. All the data that I will need will be provided for me at school on the computers. This data will include a range of different information on students from years 7-11.

Sampling

For my hypothesis I will be choosing a sampling size. I have chosen my sample size to be 50, as it will be more accurate. Also using the sample size of 50 will give me a wider range of data and therefore help me with my hypothesis more. There are various samples, which can be used. However, I am going to use random sampling and stratify sampling and this way it will avoid bias results. The random sampling will pick out my data in any order. The below formula is used to stratify my samples.

### Maths Coursework

The formula that I will use to work out my samples is:-

Number of students used in sample=

Total number of girls/boys in year X Sample Size

Total number of students in the school

Below is a table with the data which we were provided and also showing how I worked out my samples. All the samples are 0d.p

Year Group

Number of Boys

Samples for Boys

Number of Girls

Samples for Girls

Total

7

151

151/1183 x 50

= 6

131

131/1183 x 50 = 6

282

8

145

145/1183 x 50 =6

125

125/1183 x 50 = 5

270

9

118

118/1183 x 50 = 5

143

143/1183 x 50 = 6

261

10

106

106/1183 x 50 = 4

94

94/1183 x 50

= 4

200

11

84

84/1183 x 50 = 4

86

86/1183 x 50

= 4

170

The number in bold, tells me how much samples I will need from the girls and boys and it also tells me how much samples I will need from each year.

Random Sampling

After doing the stratified sample, I had to choose the students which I will use to prove my hypothesis. I will need to pick them out from the data which is provided on a spreadsheet. I will pick the samples out by using the random formula which is:-

(RAND()*150+1)

However, the number after the * changes depending on how much girl or boy students there are in that year. When I put the number in I had to minus one away and then add one back on. However, as I wanted a couple of samples for the same year and same gender, I kept on pressing F9 until I got the random amounts of students I needed. Below are all my samples which I have gathered by using the random formula:-

Random Numbers

For Year 7 Boys: – 103, 119, 89, 6, 4, 78

For Year 7 girls: – 73, 114, 30, 23, 34, 76

For Year 8 Boys: – 134, 96, 29, 60, 63, 104

For Year 8 Girls:- 39, 69,112, 36, 10

For Year 9 Boys: – 64, 11, 14, 48, 81

For Year 9 Girls: – 6, 130, 54, 101, 28, 4

For Year 10 Boys: – 66, 88, 57, 84

For Year 10 Girls: – 60, 53, 66, 47

For Year 11 Boys: – 37, 26, 8, 16

For Year 11 Girls: – 65, 50, 43, 33

Relevant Data

The table below shows the IQ and KS2 results of each student that was selected. This is all the necessary data that is needed. However I have not noted which students are from which years to make sure it is not biased in any way.

IQ

ENG

MATHS

SCIENCE

107

5

5

5

106

5

4

5

108

4

5

5

101

4

4

4

99

4

4

4

104

4

5

5

122

5

5

5

100

4

4

4

104

5

4

5

100

4

4

4

109

5

5

5

97

4

4

4

100

4

4

4

112

5

5

5

100

4

4

4

114

5

5

5

100

4

4

4

105

5

4

4

89

3

3

3

114

5

5

5

108

5

5

5

101

4

4

4

101

5

4

4

92

3

3

4

102

5

4

4

91

3

3

4

109

4

5

5

102

4

4

5

91

3

4

4

117

5

5

5

110

5

4

5

100

4

4

4

116

5

5

5

101

4

4

4

100

4

4

4

100

4

4

4

110

5

5

5

102

3

5

4

99

4

4

4

100

4

4

4

92

3

3

3

92

4

3

3

96

3

3

3

106

5

5

5

103

5

4

4

100

4

4

4

103

4

4

5

100

4

4

4

98

4

4

5

92

3

3

4

My Graph

From my samples I am going to create a graph. I have decided to do a scatter graph because; it will make it easier for me to see if my hypothesis is correct. It will make it easier for me see this, as all my points will be plotted on the graph and therefore it will give me a better understanding of my results and also a clear view of my correlation line. Below is my graph:-

From the graph you can see that my hypothesis is correct. This is because as the IQ results are going higher, so are the KS2 results going higher. I think this because, the clever you are, the more intelligent you are, as you know many things and you can gain more marks. However, from the graph you can see that there is a strong positive correlation. We can see this because, as the KS2 results are going higher, the IQ goes higher too. For example, a student who has a low KS2 result, such as, a level 3, they have a low IQ. However, if you look at the graph, a student who has got a level 5 for English, Maths and Science has got the highest IQ.

Product Moment Correlation

YR GROUP

X

Y

XY

X

Y

Yr 7 Boys

107

5

535

11449

25

106

5

530

11236

25

108

5

540

11664

25

101

4

404

10201

16

99

4

396

9801

16

104

5

520

10816

25

Yr 7 Girls

122

5

610

14884

25

100

4

400

10000

16

104

5

520

10816

25

100

4

400

10000

16

109

5

545

11881

25

97

4

388

9409

16

Yr 8 Boys

100

4

400

10000

16

112

5

560

12544

25

100

4

400

10000

16

114

5

570

12996

25

100

4

400

10000

16

105

4

420

11025

16

Yr 8 Girls

89

3

267

7921

9

114

5

570

12996

25

108

5

540

11664

25

101

4

404

10201

16

101

4

404

10201

16

Yr 9 Boys

92

3

276

8464

9

102

4

408

10404

16

91

3

273

8281

9

109

5

545

11881

25

102

4

408

10404

16

Yr 9 Girls

91

4

364

8281

16

117

5

585

13689

25

110

5

550

12100

25

100

4

400

10000

16

116

5

580

13456

25

101

4

404

10201

16

Yr 10 Boys

100

4

400

10000

16

100

4

400

10000

16

110

5

550

12100

25

102

4

408

10404

16

Yr 10 Girls

99

4

396

9801

16

100

4

400

10000

16

92

3

276

8464

9

92

3

276

8464

9

Yr 11 Boys

96

3

288

9216

9

106

5

530

11236

25

103

4

412

10609

16

100

4

400

10000

16

Yr 11 Girls

103

4

412

10609

16

100

4

400

10000

16

98

4

392

9604

16

92

3

276

8464

9

Total

?5125

?98

?21732

?527837

?904

Standard Deviation for X and Y Data

Standard deviation for IQ Results

SD = ? ? ï¿½ ? ? ï¿½

——- – ——-

n n

n = 50 (number of samples)

? ? = 5125 (whole sample added together)

? ? ï¿½ = 527837 (Square of each data point of the sample added together)

SD = 527837 5125 ï¿½

——— – ———

50 50

SD = 10556.74- (102.5)ï¿½

SD = 10556.74- 10506.25

SD = 50.49

SD = 7.105631569

SD = 7.1 (1 D.P)

The average value for the X data is:-

5125

——— = 102.5

50

This therefore, shows that my data is not reliable, as my points would not be close together. I know this because the number that I got when working out my standard deviation, it was, 7.11 and when I worked out the average mean I got 102.5 and therefore, these two numbers are far apart.

Standard deviation for the KS2 Results:-

SD = ? y ï¿½ ? y ï¿½

——- – ——-

n n

n = 50 (Number of sample)

? y = 98 2 (Whole sample added together)

? yï¿½ = 904 (Square of each data point of the sample added together)

SD = 904 98 ï¿½

——— – ———

50 50

SD = 18.08 – (1.96) ï¿½

SD = 18.08 – 3.8416

SD = 14.2384

SD = 3.773380447

SD = 3.8 (1 D.P)

The average value for Y data is:-

98

——— = 1.96

50

This show that my results for my Y data is reliable, as my standard deviation answer was, 3.77 and my average value answer was, 1.96. As the two numbers are close, this therefore proves that my data is reliable.

Product Moment Correlation Coefficient

I am now going to work out the “Product Moment Correlation Coefficient” this is normally written as, Yxy. I will work this out by using the table on the sixth page. I will work this out by using the following formula:-

?xy ?x ?y

—— – —- —-

n n n

———————————————————

?xï¿½ ?x ï¿½ ?yï¿½ ?y ï¿½

—— – —- X —– – —–

n n n n

?

SD = ? ? ï¿½ ? ? ï¿½

——- – ——-

n n

SD = ? y ï¿½ ? y ï¿½

——- – ——-

n n

Top of Yxy: – 21732 5125 98

——- – ——- x —— = 434.64 – (102.5 x 1.96) = 233.74

50 50 50

Bottom of Yxy: –

527838 5125 ï¿½

———— – ——— = 7.105631569

50 50

10556.74 – 10506.25 = 50.49

904 98 ï¿½

——- – —– = 3.773380447

50 50

18.08 – 3.8416 = 14.2384

Yxy = 2.33.74 / (7.105631569 x 3.773380447)

Yxy = 2.3374 / 26.81225123

Yxy = 0.086900573

Yxy = 0.1 (1 D.P)

Conclusion

Conclusion for my product moment correlation coefficient

From working out the standard deviation, I have concluded that my regression line has no correlation. This is because my end result which I got after working out the standard deviation my regression line was 0.0869… This therefore, shows that my regression line has no correlation. However, I am able to tell that my regression line is a positive because it is not a negative number. This shows that my hypothesis was correct, but it was not strongly proved, as my regression line was not a perfect correlation.

Overall, from the whole hypothesis I found that the higher the IQ results a student has and more likely they are going to have a higher KS2 result too. You are able to see this on my graph earlier in the work. This therefore proves my hypothesis to be correct.