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  • Level: GCSE
  • Subject: Maths
  • Essay length: 7679 words

"The taller the pupil, the heavier they will weigh."

Extracts from this essay...


Introduction Mayfield School is a secondary school of 1183 pupils aged 11-16 years of age. For my data handling coursework I have got to investigate a line of enquiry from the pupils' data. Some of the options include; relationship between IQ and Key Stage 3 results, comparing hair colour and eye colour, but I have chosen to investigate the relationship between height and weight. One of the main reasons being that this line of enquiry means that my data will be numerical, allowing me to produce a more detailed analysis rather than eye or hair colour where I would be quite limited as to what I can do. If I were to make an original prediction of my results, my hypothesis would be; "The taller the pupil, the heavier they will weigh." In this project I will consider the link between height and weight and will eventually be able to state whether my original hypothesis is in fact correct. Other factors I am going to consider when performing this investigation, is the effect of age and gender in my results and I will make further hypothesize when I reach that stage in my project. Collecting Data I have originally decided to take a random sample of 30 girls and 30 boys; this will leave me with a total of 60 pupils. I have chosen to use this amount as I feel this will be an adequate amount to retrieve results and conclusions from, although on the other hand it is not too many which would make my graph work far more difficult and in some cases harder to work with. To retrieve my data I am going to firstly use a random sample as this means that my data is not biased in any way, and all of the pupils will vary in height, weight and age - although I will have an equal gender ratio.


I have now got to work out how many girls and boys I will need from each year to make sure that my sample is a good representation of the whole school. To do this, I must consider the boys and girls separately as there are 580 girls in the school and 603 boys. When working out the year 7 sample this is what I'd do; Take the total number of year 7 girls - 131, and divide that by the total number of girls in the school, 580 ... 131/580 = 0.22586207 ... I then have to multiply that number by 30 as that is the total number of girls data I wish to obtain ... 0.22586207 X 30 = 6.7758621 ... if I then round that number up to one whole number it means that I need 7 girls from year 7 in my stratified sample. This is the calculations performed to retrieve my stratified sample numbers; Year 7 - Girls - 131/580 = 0.22586207 X 30 = 6.7758621 = 7 Year 7 - Boys - 151/603 = 0.25041459 X 30 = 7.5124377 = 8 Year 8 - Girls - 125/580 = 0.21551724 X 30 = 6.4655172 = 6 Year 8 - Boys - 145/603 = 0.24046434 X 30 = 7.2139302 = 7 Year 9 - Girls - 143/580 = 0.24655172 X 30 = 7.3965516 = 7 Year 9 - Boys - 118/603 = 0.19568823 X 30 = 5.8706469 = 6 Year 10 - Girls - 94/580 = 0.16206897 X 30 = 4.8620691 = 5 Year 10 - Boys - 106/603 = 0.17578773 X 30 = 5.2736319 = 5 Year 11 - Girls - 86/580 = 0.14827586 X 30 = 4.4482758 = 5 Year 11 - Boys - 84/603 = 0.13930348 X 30 = 4.1791044 = 4 Despite my new sample of 60 being stratified, to obtain the particular number of girls and boys from each year, I am going to select them randomly so again no biased is shown.


Although when it came to the stratified sample, and I was looking at the different age groups using again a sample of 60 trying to represent the school on a smaller scale - I do not feel it was as successful. If I were to repeat or further this investigation - I would definitely use a larger number of pupils for the stratified sample as when the numbers of the school pupils were put on a smaller scale, I only ended up in some cases with a scatter graph with only 4 datum points upon for the year 11 students. To retrieve accurate results from this method of sampling, I feel it is necessary to use a sample of at least 100. Additionally to the stratified work, if I had a larger sample - I would also produce additional graphs, i.e. cumulative frequency/ box and whisker, as I feel that I could draw a better result from these as I felt the scatter diagrams I produced were rather pointless. I feel my overall strategy for handling the investigation was satisfactory, if I had given myself more time to plan what I was going to do I think I would have come up with a better method and possibly more successful project. One of the positive points about my strategy is that because I used a range of samples it meant that I was not using the same students' data throughout - I instead used a range of data therefore maintaining a better representative of Mayfied school on a whole. There is definitely room for improvements for my investigation - if I were to do it again I would spend a lot more time planning what I was going to do instead of starting the investigation in a hurry. Despite that I feel my investigation was successful as it did allow me to pull out conclusions and summaries from the data used. Data Handling Coursework Hannah Phillips

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