Differences in wealth and life expectancy of the countries of the world

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                Maths GCSE Coursework

Maths Coursework

Introduction

For my mathematics coursework I have been given the task of finding the differences in wealth and life expectancy of the countries of the world. To my aide I shall have the World Factbook Data which was given to me by my maths teacher.    

The World Factbook Data contains the Gross Domestic Product (GDP) per capita; this is the economic value of all the goods and services produced by an economy over a specified period. It includes consumption, government purchases, investments, and exports minus imports. This is probably the best indicator of the economic health of a country. It is usually measured annually.

Another thing the data contains is the Life expectancy at birth. Life expectancy is called the average life span or mean life span, in this case of the countries or continents. This informs me of the average age a person in the specified country is likely to like to.

Using this data I shall try to prove hypotheses that I shall personally predict before carrying out the investigation.

For my investigation I shall be using varieties of different ways to presenting my data and results. I shall use graphs, charts as well as tables to make the data easier to read and understand for the reader. This would enable me also to keep organised and follow what I have to do.

To develop my work I shall use very reliable as well as advanced methods to prove my hypotheses. These shall consist of Spearman's rank correlation coefficient, box plots, standard deviation aswell as histograms.

Bearing my hypotheses in mind, I think that it would be they are irrelevant to my hypotheses and I shall gain no evidence or support from them inappropriate for me to use averages such as the mode or the range as I feel.  

My Hypotheses

:

I have chosen two hypotheses. My first Hypotheses is linked directly to my task whereas my second hypotheses is an extension task to develop my work.

My hypotheses consist of:

  • The wealth and life expectancy of a continent is linked and is likely to have a strong positive correlation. I believe this happens worldwide.

  • Females generally tend to live longer than males worldwide.

Method

I shall acquire a systematically method. This will enable my work to be organised and easy to read. First, and foremost, I shall gather all the data that is presented before me. As my hypotheses are based on worldwide data I believe it is essential for me to use all the data.

 Once I have obtained the data I shall extract the data that will be used for my investigation. For this I shall use the stratified sampling method. This method is chosen because it is a fair and unbiased method. Also stratified sampling would give me an even spread of the whole continent, not compromise of the highest or lowest sets of data (as this would give me inaccurate results of the continents).

Once obtaining the data specified I shall then separately, for each continent, put the data onto a table. I have chosen not to opt for putting the data in one big table, although my hypotheses are both related to worldwide information not separate continents, as this would narrow my results. Another advantage of putting the data onto separate tables for each continent is that I can then see which countries and continents prove my hypotheses and which countries and continents go against my hypotheses.

After having my data separated into continents I shall first draw a scatter graph for each continent. This is to get me started and show me how spread out the data roughly is.

Stratified Random Sampling

Since it is generally impossible to study the entire population (every country in every continent) I must rely on sampling to acquire a section of the continent to perform my investigation. I believe it is important that the group selected be representative of the continent, and not biased in a systematic manner. For example, a group comprised of the wealthiest countries in a given continent probably would not accurately reflect the opinions of the entire continent. For this reason I have employed stratified random sampling to achieve an unbiased sample. Using this method shall:


a)  Give me the estimates of the countries needed for each continent

b) Make selecting the data fair, as there will be no biasness.

c) Give me a more accurate result.

Firstly I used stratified sampling to find the number of countries needed from each continent, for my investigation. I deployed the formula:

Number of countries in continent

  —————————————————————————— ×60

                Total number of countries in The World Factbook Database

I multiplied the answer by sixty because that is the number that I wish to reduce the data to. I believe sixty to be the right number as it is not too big or too small and I am capable of working with that number.    

Results:

Asia: 54/235×60=14

Africa: 57/235×60=15

Europe: 48/235×60=12

Oceania: 25/235×60=6

North America: 37/235×60=9

South America: 14/235×60=4

I then randomly selected the amount presented to me for each continent. I put the countries and their given data in a graph. In some cases I had to randomly reselect a country as the previously selected country didn’t have sufficient data for me to include it in my investigation. Also for Cyprus I had to add both the Greek Cypriot area and the Turkish Cypriot area to give me the totals for the GDP-per capita for Cyprus.

Data Tables

 

Asia

Data Tables

Africa

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Data Tables

Europe

Data Tables

Oceania

Data Tables

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