Mayfield Data Handling Coursework

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Data Handling Coursework

Introduction

Ideas

My handling data coursework is concerning pupils at Mayfield High School.

The secondary data provided on each student is: Name, Age, Year Group, IQ, Weight, Height, Hair Colour, Eye colour, Distance from home to school, method of travel, numbers of brothers and sisters, key stage 2 results in maths, science and English.

My particular line of enquiry is about the heights and weights of boys and girls in all year groups.

Aims

The aim of my coursework is to observe if my hypotheses are correct and provide enough evidence to back my conclusion and interpretation in the end.

Hypothesis

My hypotheses are,

  1. My first hypothesis is regarding weight (mass): Boys weigh more than girls.
  2. My second hypothesis is regarding height: Boys are taller than girls.

Purpose

The purpose of my study is to find if boys have a larger height and weight than girls.

This line of enquiry is based on an external issue I have come across in daily life. It is the recommended daily calorie intake for boys and girls. (Shown below)

This in my opinion affects the weight of boys and girls because it indicates that boys’ recommended calories are more than the girls’.

Although there is a chance present that this theory is false as most individuals will not follow this recommendation as they can exceed or reduce the amount of calories and taking into account I am only enquiring a sample from only one school.

Enquiring the hypothesis that boys are taller than girls is based on the fact that testosterone triggers cells all over the body to grow rapidly in boys than oestrogen in girls at the teenage period.

This theory has arguments as there are late developers sometimes present that distort this theory.

Again I am only enquiring one school which will possibly result in a bias statement for the conclusion of this theory.

Plan of Action - Data collection

As the data is secondary and already been provided I will process it further to investigate my enquiries.

I will need to collect the height and weight data of both boys and girls for all the year groups.

This data will be useful in forming a conclusion and also proving my hypothesis right.

In total I will collect 60 students’ half girls and boys and they will further be divided in their year groups.

I will have to take a stratified sample from the population.

The data I will be using is quantitative data for my heights and weights and it will be continuous.

Number of Students

This table shows the total number of students and the total amount for boys and girls in each year group, in total there are 25 more boys than girls but they are varied in their year groups.

Selection

Stratified Sample

Population sample: 60 students (30 boys and 30 girls)

Boys

The Stratified Sample is rounded to a whole number to ensure the data is reliable as the number of students is discrete.

Girls

The Stratified Sample is rounded to a whole number to ensure the data is reliable as the number of students is discrete.

After gathering the stratified sample I will randomly choose the students from each year group.

The data provided is on Microsoft Excel and to obtain the random data I will use the formula =RandBetween(1,151*) This formula for example inserted in the cell will generate a random number between 1 – 151 and thus from there I will be able to generate 8 random numbers of boys in year 7.

* 151 used as a substitute for the number of boys and girls in a particular year group.

Plan of Action - Processing and Representing Data

I will group the data in two sectors Boys and Girls and each sector will contain the surnames, forenames, gender, year group, weight and height of the randomly chosen students.

I will be generating the statistical diagrams, charts and graphs by the use of ICT which is the software provided by the examining body Edexcel.

The data I had been given is not in its original form as I extracted only the variables needed and I have also put it in a table to make it clear.

Justifications

For my Hypotheses I am going to use the following methods for presentation and calculation of data,

Frequency Table: As the data is continuous for both height and weight variables I will group them in class intervals of 10 kg for weight and 10 cm for height and the table will record the height and weight of my chosen 30 boys and 30 girls and it will keep a frequency for the height and weight to be used for comparison.

Cumulative Frequency Table: This is similar to the frequency table but it will also keep a running total of the frequencies and it will base the cumulative frequency curve on this data.

Stem and leaf diagram: This will show all the individual values for the height and weight of each student to indicate the comparison of modal height and weight as well as the lowest and highest values.

Pie Chart: To signify the percentage of grouped height and weight and how it is divided up although not perfectly accurate it will signify a faint idea of the modal group of the height and weight.

Histogram: It will be useful in illustrating continuous data as it uses equal class intervals to interpret the frequency of height and weight.

Frequency polygon: It will join the midpoints of the tops of the bars of class intervals of the frequency of height and weight.

Cumulative Frequency Curve: To find the running total of the frequencies in a diagram to analyse the quartiles and the median.

Box plot: To analyze how the data is distributed out, median, central half and the range and it will be used to compare two different box plots.

Average and Spread: The results will show the average of the height and weight data for comparison and the range to identify the spread of the data. The Standard deviation will identify how far the data is from the mean average it will also be used in the comparison to see which data has higher standard deviation thus a more spread in data.

The diagram’s I will not be doing are,

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Pictogram: Basic diagrams which I predict will result in few marks and as the data is continuous it would be complicated to illustrate the data in pictures.

Tally Chart: The tally chart was substituted by the frequency table as it was more appropriate and it would show the same data.

Bar Chart: It was substituted by a histogram as the bar chart was basic and I believed the histogram was more appropriate for comparison instead of the bar chart.

Scatter Graph: This is inappropriate for my investigation as it is used to show two different sets of data on a ...

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