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  • Level: GCSE
  • Subject: Maths
  • Essay length: 1308 words

Statistics Coursework-Mayfield High School

Extracts from this essay...

Introduction

Statistics Coursework-Mayfield High School I am going to investigate the relationship between the heights and weights of the pupils in Mayfield High. Hypothesis From what I have seen in the data base and from what I have seen around my school, I predict that the taller the pupil is, the heavier they will weigh. I also think that the pupils from KS4 will be taller and heavier than the pupils in KS3. I also think that boys in KS4 will be taller than the girls in KS4. I have chosen to investigate the height and weight of the pupils because height and weight are quantitative data and they are continuous data not discrete data. I also need to collect a sample of the data to be able to analyse it properly. To do this I will take a stratified sample from the school population. The school population is 1200. There are 830 pupils in KS3 and 370 pupils in KS4. I am using a stratified sample because it will show a fair representation of the population of the school because there is a different number of pupils in each year group so just taking 50 from each group would not show a fair and proportional representation.

Middle

I could easily change this to make the data more appropriate. I will do this until I do not have any more anomalous data in my sample so that I can analyse it for patterns that give information to test my hypothesis. With the sample I will draw graphs and look for trends. I will look at trends and patterns from different key stage groups and from girls and boys and compare the results I get. I will plot histograms to see where the most information lies and compare them with other histograms to see differences in different ages and genders of pupils. I will plot box and whisker diagrams to look at the data in a way that will show how spread out it is and to compare different key stages and genders. I will plot cumulative frequency curves to see how the cumulative frequency changes as the data values increase and to see a comparison between heights and weights on the same graph to get a good comparison. I expect to get a normal cumulative frequency curve from both heights and weights. From these results I will look at my hypothesis and see how the results have tested it.

Conclusion

My diagrams and graphs show clearly that there is a trend between older boys being taller and heavier and younger girls being shorter and lighter. During my collection of information I had to adjust some of my tables and graphs due to anomalous data. As I planned, I was able to replace anomalous data and change data to make it more appropriate. My box and whisker diagrams showed clear easy comparison between age groups and genders and so were easy to compare results. I also realised once I had plotted the box and whisker diagrams that the data had a big range but almost all of the data was inside the upper and lower quartile ranges. I could have improved my sample by further by replacing some of the data that I considered appropriate as anomalous but also keeping a large range of data so that my investigation was not limited by not enough data. Also, after looking at my cumulative frequency graph I saw that the cumulative frequency curve of pupil's weight was not as defined as the curve for pupil's heights. To overcome this, I could have used a larger sample to give me more data as to plot my graphs and diagrams from.

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