• Join over 1.2 million students every month
  • Accelerate your learning by 29%
  • Unlimited access from just £6.99 per month

mayfield high. Objective To collect analyse and compare the heights and weights of boy and girl pupils in the year 10 and 11 at mayfield high school.

Extracts from this document...


Joe hughes   maths coursework


Strand 1a   planning  5

           1b  collecting 5

Strand 2a  Analysis  10



          2b  calculations 10

Strand 3 interpretations 10


  • Structured work
  • Clear diagrams
  • Accurate calculations
  • Reasons & explanations

Structured work

  • introduction
  • Question/hypothesis
  • Sampling
  • Display data
  • Comparisons
  • Correlation
  • conclutions

Clear diagrams

Accurate calculations

  • Pie charts
  • Grouped frequency table
  • histograms
  • cumulative frequency plots-box and whisker-IQR
  • Stem and leaf
  • Frequency distributions
  • Standard deviations
  • Scatter graphs- equation of line-correlation-spearmans rank correlation co efficient

 1.   Objective

To collect analyse and compare the heights and weights of boy and girl pupils in the year 10 and 11 at mayfield high school.

If i have time i would like to investigate any statistical relationships betwwen IQ level and height and or weight.

2. Plan

> My investigation is to take a representational sample of data from the 370 year 10 and year 11 pupil database provided and to use statistical methods to quantitively analyse relationships between years and genders.

> My priorety will be height, then weight then IQ data.

>i will tabulate my findings and where possible present that in graphical form for easy interprotations.

3. Specific aims

>To collect a resonable sample of pupil data, using a suitable sampling method.

>To compare gender differences for height using histogram and frequency polygon graphs, and by finding the range and three averages for each sub-group.

>To construct boy/girlheight cumulative frequency graphs for a box and whiskers group distrobution comparisons using inter quartile ranges.

...read more.


5. collecting data

The data is secondary ( not primary because i would need to collect that myself) and is part of the whole mayfiled high school (with lots of fields) available on the internet.

This table shows the number of boys and girls for the two years in which I am interested in.

Since i am interested in gender, heights, weights, and IQ only, the remainder of the fields (except names) can be filtered out.

However this would still leave me with masses of data so in order to reduce this to a manageable style, i will take


I will randomly pick samples from the spread sheet using the stratified random sample method. To avoid bids and ensure that pupils from different years and gender groups are equally represented.

My sample should be in excess of 109 to be realistic, but not so high, go to calculations too complex. I will comprimise 15%

which gets me the following numbers.

My sample data is as shown attached.

6. Representing data

The pie chart below shows the proportional breakdown of year 10 and 11 boys girls, based on.

I have decided to start by comparing boy/girl height. since height is a continuous variable i will need to produce tally tables with grouped class intervals for this purpose.

...read more.


I will draw two scatter graphs, one for year 10, and one for year 11.

These two graphs show a good possative linear

correlation between height and weight, which

backs up my second hypothesis. the lines of

best fit can be drawn, to pass as close as possible

to all parts- although there are exceptional values which fall outside the general trend.

Whilst i could find the predicted height form weigh or vice versa using my graphs, it might be simpler to have an equation.

Any straight line has an equation, Y=MX+C When C is the vertical axis intercept.

M is the gradient or shape of the line.

the equations of my lines are-

Boys H =MW+C

Girls H =MW+C

I can use these to make a prediction e.g for boys weight _______ height______

                                                                   girls weight________ height______

at first glance it appears that _______ have better correlation, ie less offsets, from my lines of best fit.

however i would like to quantify this- using spearmans rank correlation coefficient. this will be ranged from 0 for correlation to 1 for points and straight line (perfect correlation)

To reduce my correlations on year 11 first boys I will eventually do for all sub sectors.

Boy name height-rank and weight-rank  d d2













 girls name height-rank and weight-rank d d2












12         This quantities my ''gut feeling'' since it shows boys with _____ correlation and girls with _____ correlation. (see statistics textbook page 176)

...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. Marked by a teacher

    Height and Weight of Pupils

    Female 1.6 42 9 Tucker Jayde Female 1.57 40 9 Zigo Zanuub Female 1.75 56 10 Ashiq Azra Female 1.60 56 10 Bhatti Sadia Female 1.62 48 10 Campbell Debbie Female 1.55 55 10 Johnston Summer Female 1.50 40 10 Khaliq Nazia Female 1.62 48 10 Razwana Tahira Female 1.62

  2. mayfield high statistics coursework

    65 70?w<80 0 75 0 TOTAL 20 895 Mean = 895 divided by 20 = 44.75 rounded off to 45 kg for GIRLS Mean of Boys and Girls Height BOYS Height (cm) Tally Frequency Mid-point Fx 130?h<140 II 2 135 270 140?h<150 0 145 0 150?h<160 IIIIII 6 155 930

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

    However the median for the girls is higher than the boys, also the range of the girls 0.56m is much more spread out compared to 0.4m for the boys. The evidence from the sample suggests that 13 out of 25 or 52% of boys have a height that is between

  2. Mayfield High Statistics Coursework

    metres this shows me that I have a neutral skew of my data. Boys Weight (kg) Frequency 20?w<40 4 40?w<50 18 50?w<60 16 60?w<70 8 70?w<90 4 This tally frequency table shows that like the heights the boys weight has a near perfect neutral skew, it has very high frequencies

  1. Liquid chromatography is a technique used to separate components of a mixture to isolate ...

    It was ensured that the solutions were made before this occurred. * The scope of this project is extremely large and if time was not a limitation it could be extended further.

  2. I would like to know whether there is a link between ability in Maths ...

    line which is above the y = x would confirm that the students, on average, showed a greater ability in Science than in Maths. Below is a table to show the result of my calculations: Least Squares Regression Line Males Females y = 0.48 + 0.90x y = 1.25 +

  1. we can see if there is any correlation between a person's height and weight ...

    then times it by the amount of samples you want to work with, in this case its 60. e.g. number of students in each year Total amount of student in the school x 60. 282 1183 x 60 = 14.3026 Year 7 270 1183 x 60 = 13.6939 Year 8

  2. Rapid ascent to high altitude (2500m or more) can result in the development in ...

    27 2.4 Basnyat Gosaikkund 4300 228 68 - 4.8 Nepal Cremona Monte Rosa 4559 262 - 15 0.4 Italy (Sonna, 2002). As can be seen from figure 2 the number of people who contract AMS is high with a mean value of 49.5 % � 14.6 %, however the number

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