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• Level: GCSE
• Subject: Maths
• Word count: 1904

# My hypothesis is that the Maths and Science results will be related because I think if a male/female is good at Maths he/she will also be good at Science.

Extracts from this document...

Introduction

For my second piece of coursework, I have being given 300 pieces of original data about students in an unknown school. This data includes year, gender, class and test results in English, Maths, Science and French. This data is too big to manage so I have decided to take a random sample of 30 students from each year. 15 females and 15 males.

I will look at each year group in turn and from there I will create a table of the numbers contained in each class, in each year group.

 Year Gender:Male Female Class 8 14 12 A 8 14 11 B 8 13 8 C 8 14 10 D 8 9 15 E Total 56 64 120 in year 8
 Year Gender:Male Female Class 9 10 17 A 9 10 16 B 9 12 5 C 9 6 4 D Total 42 38 80 in year 9
 Year Gender:Male Female Class 10 5 20 A 10 16 10 B 10 14 10 C 10 13 12 D Total 48 52 100 in year 10

Check: -

Year 8    = 120

Year 9    = 80

Year 10  = 100

Total               300

Now I am going to select the 15 males and 15 females systematically.

My hypothesis is that the Maths and Science results will be related because I think if a male/female is good at Maths he/she will also be good at Science.

I am going to draw scatter graphs and frequency tables to see if there is a correlation between the Maths and Science.

...read more.

Middle

0

95

0 × 95

0

I decided to use scatter graphs because they are the easiest diagrams to draw when comparing the Maths and Science results.

I have drawn a line of best fit because it allows me to predict a mark if a student misses a test.

Example:

A student in year 10 scored 60 in a recent maths test, but he/she missed a science test the day after. I predict that the student would score 63 in his/her science test if he/she were there.

I do this my going to the maths scores for Year 10 in my scatter graph and going to 60 and would then go up in a line and I would hit the line of best fit and go across and the mark is 63.

After looking at the graph for Year 8, I found that their marks were tightly packed together, which shows strong positive correlation.

After looking at the Year 9 and 10, I found that both their marks were tightly packed together, which again shows strong positive correlation.

I am going to examine each year group in turn and draw frequency tables for each year group and subject.

## Smallest and Largest values

 Year 8 Year 9 Year 10 Maths Science Maths Science Maths Science 41 43 36 41 30 35 43 48 42 44 39 38 44 48 43 47 40 41 47 49 43 47 43 42 52 50 44 47 45 43 52 53 47 50 45 44 52 55 49 51 48 46 52 55 50 51 48 48 54 56 52 51 50 50 55 58 54 52 52 52 56 59 55 52 53 52 56 61 56 53 57 53 57 62 57 54 57 56 59 62 58 54 58 57 60 62 59 56 60 60 60 62 59 56 61 62 61 63 62 57 62 65 62 65 63 59 63 65 62 66 63 59 64 65 64 66 64 59 66 65 65 70 65 62 67 66 65 70 67 64 68 68 67 71 70 64 68 69 68 72 72 68 70 72 68 74 72 69 70 72 68 76 74 70 71 74 73 78 75 70 74 80 75 80 76 71 76 82 78 80 80 76 76 83 83 90 80 78 79 84

My results so far have confirmed my first hypothesis, which is that Maths and Science are closely linked.

## Second hypothesis

I will now investigate the differences in gender may effect the marks in a particular subject like Maths.

Again to further my investigate, I am going to use Stem and Leaf diagrams to compare female marks with male marks. A Stem and Leaf diagram consists of numbers, which themselves made up the bars, like in a bar chart. I have already systemically chosen a sample of 30 students from each year group, again 15 females and 15 males.

By doing this it avoids bias and will represent the complete data given. A Stem and Leaf diagram is used to display data in order of size. It can also be used to find the mode, median, lower quartile, upper quartile and interquartile range.

### Year 8 Maths

 Females Males 30 40 50 60 70 80 30 40 50 60 70 80 43 52 60 73 41 52 60 78 83 52 62 75 44 55 61 52 64 47 56 62 54 65 59 67 56 65 68 57 68 68

Stem and Leaf

 Females Stem Males 30 3 40 1 4 7 7 6 4 2 2 2 50 2 5 6 9 8 5 5 4 2 0 60 0 1 2 7 8 8 5 3 70 8 80 3
 Females Males Mean 59.3 60 Median 60 60 Mode 52 68 Range 32 42
...read more.

Conclusion

59.9

58.6

Median

64

58

Mode

45, 70

48, 57

Range

37

49

From this set of results I have noticed tat the girls in year 10 are better than the boys at Maths. For example the girls have achieved a higher mode, which is 45, 70 and the boys mode was 48, 57. They also had a higher mean and median.

I am now going to construct Box and Whisker diagrams, these will show the distribution of data.

First of all I will find the biggest and smallest values. Then I will put Year 8, 9 and 10 Maths and Science marks in order of size, starting from the smallest to the biggest, from here I will need to obtain each year groups median and lower and upper quartiles.

This box shows the Mean for each year group.

 Year Maths Mean Science Mean 8 60 63 9 60 58 10 59 57

From the results in the table above I can see that the means are quite close together.

#### Year 8

 Maths Science Median 60 62 Lower Quartile 52 55 Upper Quartile 67 71 Lowest Value 41 43 Highest Value 83 90

#### Year 9

 Maths Science Median 59 56 Lower Quartile 50 51 Upper Quartile 70 64 Lowest Value 36 41 Highest Value 80 78

#### Year 10

 Maths Science Median 61 62 Lower Quartile 48 48 Upper Quartile 68 69 Lowest Value 30 35 Highest Value 79 84

From the box plots I can see that Year 8 are slightly better at maths and science than Year 9 and 10.

 Year Maths Mean Science Mean 8 60 63 9 60 58 10 59 57

From the results above

...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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