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Statistics Coursework-Mayfield High School

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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.

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Middle

Total

250

To select the pupils in my stratified sample from the school population I will use random numbers. The random numbers I use will be from a calculator and will be completely random and will not be biased in any way. The pupils have allocated numbers in the Microsoft excel file and so random numbers will be used to select the pupils I need for my stratified sample.

Once I have taken my sample, I will look at the data to analyse it. I will look for anomalies. If I find any then I will replace them with data from the database. I will randomly collect data to replace anomalous data if I find any. If I can see what is wrong with the anomalous data I will replace it myself for example there may be a typing error of 170m instead of 1.70m. 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.

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Conclusion

 has generally been proven to be correct. 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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