• 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
  12. 12
  13. 13
  14. 14
  15. 15
  16. 16
  17. 17
  18. 18
  19. 19
  20. 20
  21. 21
  22. 22
  23. 23
  24. 24
  25. 25
  26. 26
  • Level: GCSE
  • Subject: Maths
  • Word count: 5980

Mayfield High School

Extracts from this document...


GCSE Statistics Coursework Introduction: Mayfield High School is a fictional secondary school where all the students are surveyed about their body, habits, likes and dislikes. My task will be to test my hypotheses using a variety of statistical techniques and analysing my findings. The data I have been provided with is secondary data. This is data previously gathered by someone else and has been made and accessible or has been published so that it can be used by someone else. This therefore means, it is not primary data- which is data collected by the researcher (me) specifically for this project. Hypotheses: To work out a person's BMI, we take their weight in kilograms and divide it by the square of their height in metres. I travel 3km to get to school. My height is 1.65m and my weight is 65kg. Therefore, my BMI (Body Mass Index) is 24. My friend, who travels 0.5km to get to school, has a BMI of 28. This has given my hypotheses: i) Students who have to travel further to get to school will have a higher BMI compared to those who don't have to travel as far The probability of a longer journey home compared to those who live closer to school is very high. During a bus or car journey, it is likely that the student will eat snacks. When they get home, the chances are that they will watch TV, eat dinner, do homework and play on the computer. It is highly unlikely that they will get round to exercise. ii) Students who travel further to get to school would be taller than those who live closer would would. I expect those closer to the school to have a lower BMI. Ultimately, I expect them to be taller or lighter to reduce their BMI. iii) Students who live closer to the school are lighter than those who live further away are. ...read more.


This means interpreting data will be very easy. It is also used because I summarising ordinal data. When drawing the bar chart, I shall ensure that: i) An appropriate scale is used A bar chart with an inappropriate scale can be very misleading. It can suggest unreal failures, successes or correlations. ii) All the bars are of the same width If bars are not of the same width, then the graph can also be very misleading. It can suggest opinions and therefore be biased. iii) All the axes are labelled If the axes were left unlabelled, the reader will not know what the bar chart is representing. iv) Both axes start on zero False zeros are used to present correct but misleading data. As I do not wish to lead the reader into any conclusions, my axes will start at zero. Bar Chart Calculations I will plot the mean of each group, rather than the median. Using the mean will allow me to work with all of the data in each group and the mean is probably the most accurate average. Therefore, I will not be excluding any results and therefore not causing any sort of bias. However, I accept that the mean itself may not be a true value and that it may be distorted by any extreme values. Students that live with 2.9 kilometres of the school: 15.6 + 18.5 + 16.6 + 20.8 + 18.0 + 24.0 + 27.1 + 24.8 + 15.7 + 20.1 + 18.3 + 21.5 + 18.2 + 16.0 + 16.0 + 17.9 + 19.6 + 24.8 + 17.4 + 24.8 + 17.4 + 21.1 + 17.2 + 19.5 + 23.0 + 14.8 + 16.9 + 17.3 + 18.1 + 18.3 + 19.9 = 578.3 578.3 / 30 = 19.3 Students that live between 3.0 miles and 4.9 miles of the school: 20.0 + 16.8 + 16.6 + 18.2 + 19.4 + 20.6 + 17.6 + 18.6 + 28.9 + 23.8 = 200.5 200.5 / 10 = 20.1 (3SF) ...read more.


To obtain someone's IQ, you could give them a test based on pictures or give them a written test. We are not told that every single person in the Mayfield database had their IQ tested in the same manner. Also, distances to and from school could be estimates rather than precise measurements. There is no doubt that my conclusions could be incorrect. Sample sizes: Overall, I feel that the sample sizes I have used for each part of my project are very sensible. I have not had to spend ages manipulating the data and plotting graphs. This shows that I have not taken a sample which is too large. However, my graphs and calculations were not done very quickly either, although they did not take hours, they still took some time. I feel that my sample sizes were not too small. My hypotheses: Overall, I feel that I have satisfied my goals on the first page. I have used a range of statistical skills, techniques and data representation methods to try and prove or disprove my hypotheses. In general, I feel that my work could have been improved if I had taken a sample double the size of all of the ones that I have done. I feel that would have made outliers more obvious and therefore given me a clearer statement on the quality of the data. I am happy that my conclusions are reliable because they were blatantly obvious. For example, it was obvious from the composite bar chart that the distance travelled to get to school had no impact on your height. My findings: As a result of my sampling, calculations, and data representations, I can state the following: - Those who live closer to Mayfield High School have a lower BMI - Those who live further to Mayfield High School weigh more. - Those who live closer to Mayfield High School are just as tall as those who live further away from the school. AQA GCSE Statistics Coursework 1 Vinson Yeung 10W King Edward VI Camp Hill Boys ...read more.

The above preview is unformatted text

This student written piece of work is one of many that can be found in our GCSE Height and Weight of Pupils and other Mayfield High School investigations 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 GCSE Height and Weight of Pupils and other Mayfield High School investigations essays

  1. mayfield high statistics coursework

    Frequency Polygon and a Histogram that shows the Boys & Girls Height and Weights From my sample that I have taken a for my assignment. The Frequency Polygon will clearly identify the shape of my variations and both these forms of representing data will help me form a sufficient analysis.

  2. Conduct an investigation comparing height and weight from pupils in Mayfield School.

    together in order to make there frequencies large enough to plot on a histogram. This indicates that before any combining of intervals was made that the most popular intervals were in the middle intervals of my data. Then I did frequency density so that I could compare boys against girls for height and weight.

  1. Statistics GCSE Coursework. Height and weight of pupils. The sampling method I am ...

    Percentage increases in mean height and weight (females): Mean Height (m) Mean Weight (kg) Year 7 to year 9 (1.58-1.56)�1.56�100 =1.28205% (47.2-44.77)�44.77�100 =5.42774% Year 9 to Year 11 (1.64-1.58)�1.58�100 =3.79746% (48.77-47.2)�47.2�100 =14.82572% Percentage increases in mean height and weight (males): Mean Height (m)

  2. Mayfield High School

    The mode is simple; you just find the group with the highest frequency. I am now going to find the mean, median and mode of the IQ and Ks2 results. To make it easier for my I am going group the data up.

  1. Maths Data Handling

    mx + c' by finding the gradient of the line and the y-intercept. The y-intercept will need to be worked out as I do not have a graph with two quadrants or an origin. This is done by working out the gradient, putting in any values for x and y

  2. I will be testing the following hypothesis in my pilot study: ...

    and identify these outliers and decide what measures to carry out (replace them or leave them as they are). I am also going to show the graphs before and after the calculations for the anomalies to show the graphs with the outliers and also without the outliers.

  1. mayfield high school handling data coursework

    Willes Philip Male 1.55 32 0.232391 7 Sammy Singh Amrit Male 1.52 54 0.162274 7 Hagrid Davison Male 1.75 62 0.310806 7 Seedat Sajeed Robert Male 1.65 46 0.542554 7 Ashcroft Wayne Paul Male 1.52 37 0.644392 7 Green Thomas Male 1.54 38 0.82478 7 Langly Shane Male 1.50 40

  2. Maths - Mayfeild High School

    and help me form a strong conclusion to relate to my Hypothesis. It will also show me the averages of heights and weights of females and males of the school Mayfield high school. 1. I will plot the heights and weights of the 60 students on a scatter graph, and

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