• 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. Maths GCSE Statistics Coursework

    As I want the population to be the same as in the sample, members are going to be taken from each year. In year, 7 there are 75 males and 98 females. In year, 11 there are 93 males and 85 females.

  2. Statistics coursework

    This is for the same reasons as I used the same type of graph in the first part of my investigation. As before, I will use a box and whisker to show the same data as on the graph but with extremes being made obvious.

  1. Statistics. The purpose of this coursework is to investigate the comparative relationships between the ...

    If this is right, my first hypothesis will be correct, and I will proceed in analyzing the other graphs for my hypotheses. My data is quite grouped, so I expect to see some form of positive correlation. My hypothesis is correct: my graph has a positive correlation.

  2. Intermediate Maths Driving Test Coursework

    1/4(41+1) 10.5th observation Upper Q= 3/4 (n+1) 3/4 (41+1) 31.5th observation Range= 33 - 2 Females Number of minor mistakes Q1 10.5 Q2 15 Q3 23 Range 31 Minimum 2 Maximum 33 Males Number of minor mistakes Q1 6 Q2 13 Q3 21 Range 30 Minimum 1 Maximum 31 We can see from the box plot above that the

  1. Descriptive Statistics 1. Mean, median and mode.

    will exactly cancel out the sum of positive differences (from scores that are greater than the mean). The sum of deviations from the mean is always zero. Sum of Squared Deviations Positive and negative deviations from the mean cancel out when you sum them.

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

    Finding the Mean, Median and Mode In order to find the Mean, I will add all of the attendance numbers together, and divide the number of sets of data I recorded; Birmingham City Mean: 21,394 + 27,333 + 22,186 + 23,138 + 26,850 + 26,474 + 24,357 + 25,770 +

  1. Fantasy Football - Maths Coursework - Statistics

    I have also included the cumulative frequency graph and the box plots that I drew for this hypothesis. Table for cumulative frequency: Points Tally Frequency Cumulative Frequency 0 ? P < 30 |||| 4 4 30 ? P < 60 |||| 4 8 60 ?

  2. Teenagers and Computers Data And Statistics Project

    just be 1 at every measurement .It would also only have 6 faces 4. Predictions of a 6 x 6 x 6 cube. Once I had half filled in my chart , with the 2,3,4 chart I was quite sure that I could see a few patterns within the data.

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