• 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
  • Level: GCSE
  • Subject: Maths
  • Word count: 1446

Analysing the data sheet which contains all the data of the student's weight and height, both male and female.

Extracts from this document...


Year 10 math handling data coursework


The background objective of my study is to investigate my hypothesis (which will act as a basis for my findings) this will be carried out by analysing the data sheet which contains all the data of the student’s weight and height, both male and female.

I will then portray the data onto a number of sampling techniques I found in a text book so when I collected my data I will be using the following: scatter diagrams, line graphs, histograms, cumulative frequency tables, bar charts and frequency polygon.

This will make it much easier for me to conclude and will also be clear to others who come across this information when via these mediums it is presented onto a simple graph. After this data has been recorded, I will overlook my hypothesis and analyze if it concur add up. If not then my hypothesis was obviously wrong and misleading.

I will then make the correct hypothesis so that it corresponds with my graphs.

...read more.



Bar chart.image07.png





Scatter diagrams

                       Diagram A.                                                            Diagram B.


I have made two different sorts of scatter diagrams with the same data. Diagram A is not in ascending order whereas diagram B is in ascending order with the lowest heights to the highest. On diagram B, there is no need for me to place a line of best fit as it is already in order and shows a strong and positive correlation whereas surprisingly diagram A, which is the same data shows a weak negative correlation.

Y = mx + c





Y = mx+ cis the general equation for a straight line graph.

“M” is equal to the gradient of the graph        “C” is the value where it crosses the y-axis and is called the intercept.

These are cumulative frequency tables which I have produced

...read more.


3/4 of the total frequency, we can read estimates of the lower quartile, median and upper quartile from the horizontal axis.

I have drawn on the lower median and upper quartile.

The shape of the cumulative frequency curve tells us how spreads out the data values are.


I have made two other cumulative frequency graphs with the same male data. I wanted to see if the data’s conclusions could be seen in a different and possibly clearer way. I think that the 3D graph is a clear visual of the data presented.


I used Microsoft office excel to make all these assorted graphs and charts. These help me and others to understand the data easier and for those who are weak at maths, it will be clear to them when the data is presented on a simple graph.

Interpreting and discussing results

 I set out to find out if…

 “Males are taller then females in year 10.” I found out that my original hypothesis was indeed correct. I used a various number of collected graphs and charts, in which these helped me in finding out if my assumptions were accurate and correct.

I found this out by collecting the data that I needed

...read more.

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. I am going to find out the year 10 male average student at Weavers ...

    Also there were 83 males in the year of 1996. 30/83 is 36% of the total no. of year 10 males which is small enough to be manageable and yet be representative. I am going to use systematic sampling because it is non biased, uses all the data and is quick unlike quota sampling which often can be biased.

  2. Maths Data Handling

    that there is a relationship, which will be looked at further on in the investigation. However, I think that the range that was found is quite unreliable to use in the conclusion. This is because the two extreme values created a big range, especially for the boys, meaning that the

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

    I will take a stratified random sample of 100 students for my pilot study. This is because there will be an amount from each year group and that it is a fair proportion to take from the whole population of 1183 students.

  2. Maths: Data Handling Coursework

    This could be showing that girls aren't growing as fast. Year 9 Girls (Total of 60) Weight (kg) Year 9 Boys (Total of 50) 988765 3 5889 988888887776665555522100 4 222245555789 9987766555442222111000 5 000001111244558 8655200 6 000235666688 42 7 002455 9 0 This diagram shows the weight of pupils in Year 9.

  1. Mayfield data handling

    The initial sample that I will use to look at is 15 students, regardless of gender, from each KS2 results. In order for me to do this, I used the random button on my scientific calculator to get random numbers of students.

  2. Maths newspaper data collection project

    and then multiplying that number by the amount of percent that each section is. I rounded the amount of sentences up or down depending on whether the number after the point (The first decimal place) was above or below five.

  1. Maths data investgation

    I Attendence (%) Sex Maths (%) 73.1 F 56.8 74.4 M 65.7 75.6 M 55.2 69.2 F 43 92.6 F 100 96.6 F 100 80 M 59.8 82 M 46.8 76.1 F 49.4 82.4 M 36.9 85.9 M 41 75.8 M 39 86.8 M 57.8 69 M 59.3 92 F 79.9 58.8 F

  2. Testing 3 Hypotheses on Pupils Height and Weight.

    Girls develop earlier than boys however there are some boys that are still very tall. This is why I think that the boy's average is higher because I choose to use mean to calculate the average. Using mean means that if there are a hand full of students who are tall they will put the mean up.

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