For my Statistics coursework I have decided that I will compare weight and height. I will use the data that has been gathered from Mayfield high school and I will show various methods to prove my hypothesis correct.

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Sara Sherwani 10C

Statistics Coursework

GCSE Data Handling Project – Mayfield High School

Introduction

For my Statistics coursework I have decided that I will compare weight and height. I will use the data that has been gathered from Mayfield high school and I will show various methods to prove my hypothesis correct. The data that I have collected is secondary data this means that it has been accumulated by someone else this could make the data unreliable. However, after evaluating the source of the data and seeing that even though primary data may be more accurate I have come to the conclusion that using secondary data would be more useful because primary data would take too long to get the vast amount of data needed to get accurate results.

When conducting my investigation I went through various stages

Hypothesis 1

Year 7s will not be as tall as the Year 11s

I have chosen this hypothesis because I think it is the most likely to be correct. From my personal experience being in a high school I can already observe the height differences between the younger children and the older. This hypothesis will result in a positive correlation.

Hypothesis 2

Females will have a higher BMI (Body Mass Index) than males

I think this hypothesis will be correct because I know that when girls go through puberty they develop more fat especially around the hips and waist. This is due to the natural course that every girl will go through. Also I know that males lose weight and gain more muscle tissue quicker than girls.

 

I am going to use the formula shown above to work out BMI.

Hypothesis 3

The taller you are the more you will weigh will result in a strong positive linear correlation

I have opted to use this hypothesis because I think that it will show a positive correlation. To display this I am going to use Spearman’s rank correlation coefficient because this will prove whether the correlation is either weak or strong depending on if it is negative or positive.

Data Validation

In data validation I was making my data more precise and therefore had to delete and clear out any information that would be irrelevant in my data. This included deleted all data that was an outlier.

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To detect outliers I had to use a specific formula. If I had just deleted my data by hand there is chance that I might miss some data and therefore make my data inaccurate.

For example

To find out any outliers that are under 29 I have used this formula:

=IF(J3<29,”outlier”)

This enables the word “outlier” to appear next to a figure if it is under 29.

To find out any outliers that are over 69 I have used another formula this is:

=IF(J10>69,”outlier”) ...

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