• Join over 1.2 million students every month
  • Accelerate your learning by 29%
  • Unlimited access from just £6.99 per month
  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10
  11. 11

GCSE Mathematics Coursework: Statistics Project

Extracts from this document...


Chioma Oganya, 11F Tiffin Girls’ School

GCSE Mathematics Coursework: Statistics Project


Mayfield is a fictitious High School that features data on the 1150 pupils in Years 7 – 11.  The data presented is based on a real school and includes information such as gender, year group, IQ, height and weight for each pupil.  My aim is to analyse this information to prove the following hypothesis:

The more hours of TV watched per week, the greater the weight of the pupil.

Justification of Hypothesis:

It is logical to assume that the more time spent sitting in front of the television, the less time spent on active activities such as exercise and sport.  Therefore, I think that people that watch large amounts of television will be more unfit and will consequently weigh more as they have not participated in much vigorous exercise to ‘burn off’ fat.

Table showing the Number of Boys and Girls in each Year Group of Mayfield High School

Year Group

Number of Boys

Number of Girls


Year 7




Year 8




Year 9




Year 10




Year 11








With a database featuring 1150 pupils, it would be impractical to analyse the entire database considering the time constraints.  I will need to take an appropriate sample so that I can analyse the information to come to a reliable conclusion.  A sample of 100 pupils is appropriate as it is large enough for any findings to be reliable (in contrast, if a conclusion was formed using data from only six pupils for example, then it would not be reliable as the sample would not be fully representative of all the pupils in the school).  It is important to make sure that the sample is not biased, so that the conclusion is reliable.  The school features Years 7 – 11 and in each year, there are different numbers of girls and boys.

...read more.




to get random numbers ranging from 0 < x ≤ 276.  276 must be used rather than 275, as Row 1 is used in every Excel sheet for the list headings, rather than holding a pupil’s data.  Therefore, if the number ‘1’ was randomly generated, it would be ignored and the random number ‘276’ would mean I would take the pupil in Row 276, which would be pupil no. 275.  Obviously, I will continue to take pupils in Year 7 until I have 13 boys and 11 girls.  If, for instance, a number is generated where the pupil is female even after 11 girls have already been selected, then the number will be ignored.  Otherwise, the proportions of girls and boys in the sample would not represent the proportions present in the Year Group.  Also, as the random numbers generated can be up to three decimal places, they will be rounded to the nearest whole number.

After performing this process for Year 7, the same will be done for each Year group to select the pupils.

I have now collected my sample, which is shown overleaf:

In order to test whether there is a relationship between the average amount of TV watched per week and the weight of a pupil, I will construct a scatter graph.  Scatter graphs are effective in discovering whether there is a correlation between two sets of data, as one set of data is plotted on the x-axis and the other on the y-axis.  A line of best fit can also be drawn and the r-value can be found using Excel to describe how strong the correlation is.  For my scatter graph, the average hours of TV watched per week will be on the x-axis, as my hypothesis states that this will determine the weight of a pupil.  

...read more.


Conclusion – Has my hypothesis been proved or disproved?

It has been proved to a certain extent.  The Year 7s and Year 8s in the sample show that the more TV a pupil watches, the more he/she weighs.  However, Years 9-11 show otherwise and when looking at the relationship between the amount of TV watched and weight for the sample of 100, it appears that the more TV pupils watch, the less they weigh.  Gender has also proved to affect the relationship, with girls generally watching slightly more than boys but weighing less.

what do I want 2 do         – analyse weight using mean + standard deviation

  • analyse the amount of TV by doing a box and whisker diagram.. to find the median + the interquartile ranges, first will group the data into categories + will do cumulative frequency diagrams, one for the females + one for the males.
  • Then do the years…

The graph shows….Grouping the 100 pupils together might hide differences between different groups, such as females and males.  To discover whether there is a difference in correlation between the boys’ weight compared to the amount of TV watched and the girls’ weight and the amount of TV watched, separate scatter graphs will be plotted for the 51 boys and the 49 girls…

  • note the differences in r-values
  • also note that the girls generally watch far less tv – this will be interesting to analyse in a box + whisker + cumulative frequency diagram.

Fall back on this:

This graph features data from all the people in the sample of 100, so the results may hide slight differences between certain groups ie girls may generally watch more television than boys, or there might be a stronger correlation between amount of TV watched and weight for Year 7s than Year 11s.  In order to investigate this, I will first test whether there is a difference in the relationship between the amount of television and weight for boys and then girls, by doing one scatter graph for the 51 boys and another for the 49 girls.

...read more.

This student written piece of work is one of many that can be found in our AS and A Level Probability & Statistics 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 AS and A Level Probability & Statistics essays

  1. Statistical coursework that uses data from 'Mayfield High School.'

    However, the size of the sample of each category does not reflect the population as a whole. This can be used where an unrepresentative sample is desirable (e.g. you might want to interview more children than adults for a survey on computer games), or where it would be too difficult to undertake a stratified sample.

  2. Investigate if there is any correlation between the GDP per capita ($) of a ...

    Congo, Democratic Republic of the 600 1.689575216 Cote d'Ivoire 1400 1.629919036 Djibouti 1300 1.634779458 East Timor 500 1.814247596 El Salvador 4600 1.848927713 Ethiopia 700 1.615318657 French Guiana 14400 1.884738738 Gambia, The 1800 1.735439203 Ghana 2000 1.752278985 Grenada 5000 1.809694359 Guatemala 3900 1.814447379 Guinea-Bissau 700 1.67182056 Honduras 2500 1.823800154 India 2600

  1. Maths GCSE Statistics Coursework

    Stratified Calculations Total number of year 7 pupils asked = 173. Year 7 boys 75 �50 = 21.6, choose 22. 173 Year 7 girls 98 �50 = 28.3, choose 28. 173 Year 11 boys 93 �50 = 26.1, choose 26. 178 Year 11 girls 85 �50 = 23.9, choose 24.

  2. Statistics. I have been asked to construct an assignment regarding statistics. The statistics ...

    Although 41 thousand occurs the most, I feel this cannot be the mode because the 'hundreds' after the 41, are not the same. For example; 41,752 and 41,752 would be the mode if this occurred twice, but 41,752 and 41,761 for example are not the same number, although a close match, there is not mode.

  1. Statistics coursework

    11 girls 86 Year 11 boys 84 452 - population Proportion of strata Rounded number Year 7 girls 57.96460177 58 Year 7 boys 66.81415929 67 Year 11 girls 38.05309735 38 Year 11 boys 37.16814159 37 - With sample size of 200 I feel this is an appropriate sample size as the lowest proportion is just over 30.

  2. Statistical investigation into pupils at Mayfield high school

    Girls Year No. in Year Calculation No. of pupils taken to create sample 7 131 131/1183x50 6 8 125 125/1183x50 5 9 143 143/1183x50 6 10 94 94/1183x50 4 11 86 86/1183x50 4 Boys Year No. in Year Calculation No.


    Stratified sampling is when the population is divided into groups, in this case, year groups. Then from each strata, you randomly select the number of pupils from that year. Below is a table showing the number of boys and girls in each year.

  2. Mayfield High School Maths Coursework

    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

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