Male And Female School Life Expectancy example essay topic

Statistics Coursework Aims... For my statistics coursework I intend to carry out an investigation to discover if there is a relationship between two sets of data. I will use a range of appropriate statistical measures and calculations which will allow me to discover whether there is a relationship between the two sets of data. I am trying to discover if there is a link between the per capita gross domestic product of a country and the school life expectancy of a citizen in that country. Allow me to explain the two different statistics. Per capita gross domestic product is measured in US dollars and represents the gross domestic product for each citizen of the country that is fifteen or over and economically active (i.e. earning money) over a period of a year.

Per capita gross domestic product is basically the average amount a working adult earns per year in that particular country. Gross domestic product is an average calculated by the statistics division of the United Nations. School life expectancy is also an average calculated by the United Nations statistics division and represents the average number of years schooling a child can expect to receive in any given country. I will select a number of countries at random and then I will analyse both sets of data for each country allowing me to draw conclusions about the relationship between the two sets of data. Hypothesis... I believe that the school life expectancy will increase as the per capita GNP does.

This is because richer more developed countries have more money to spend on education. I will investigate this... I will try to discover if males receive a longer education (in years) than females. Or if females receive a longer education than males. I believe that in a percentage of countries males will receive a longer education... As I have got the data for both male and female school life expectancy I will calculate an average of the two, which I can use in some of my calculations.

Data... For my investigation I have collected secondary data. After looking through various books and on different Internet sites I found the data I was looking for at web This is the web site of the statistical division of the United Nations. I believe that the data I have obtained is reliable because I have collected it from a reputable source and it is an average, which is generally more reliable. I chose to do my investigation on these two sets of data because I found them interesting. The statistical data was freely available and relatively easily to obtain.

When I first accessed the data it was for every different country in the world and therefore I needed to reduce the sample size. I did this by picking twenty countries completely randomly. Taking a random sample is fair. To take a random sample I placed each country's name in a opaque bag and shuffled them so I would not be able to tell which one was which while they were in the bag. Then I picked twenty different countries out at random. I did not encounter any problems while I was collecting my data.

School life expectancy is given for both male and females so I have decided to calculate an average of the two for each country. I have decided to display my data in a table. I believe a table is a good way of displaying the data because a table is easy to read and understand. A table shows the data clearly and makes it difficult to confuse different bits of my data.

I am expecting quite a large range of readings due to the diversity of different countries around the world that I have selected in the random sample that I took. I am expecting per capita GNP to range from around two hundred US dollars to around twenty-eight thousand US dollars. I don't expect to see much difference between male and female school life expectancies. However I expect male school life expectancy to range from around four years to around eighteen years and the same for female school life expectancy. Data I have collected and selected... The table I have used makes the data easy and clear to read.

I have sorted it so that the countries with the highest GNP per capita (in US dollars) are at the top and the countries with the lowest GNP per capita are at the bottom of the table. They are in descending order with the highest first. Displaying them in this way makes the data easy to read and it makes it easier to make comparisons when I conclude the investigation. The table shows me in a rank order which countries have the highest GNP per Capita.

I have sorted it so it displays average school life expectancy in a descending order. Displaying the data like this makes it easy for me to see which countries have the highest school life expectancy and it allows me to draw conclusions with greater ease. Calculations... 1.

I found the average or mean school life expectancy and I have displayed my results in the previous table along with my results. Here is an example of how I calculated the mean: This is how I found the mean for Australia, Firstly I took the male and female data and added them together in this case it was 17.1+17.1 = 34.2. Then I divided the sum of the data by the number of pieces of data e.g. 34.2/2 = 17.1. I then repeated this process for the rest of the data in the table. Then displayed the results in the right hand column of the table.

2. I am going to find the average amount of education a male receives. I can do this by adding all of the data up and dividing it by the number of pieces of data. I then repeated the calculation for females. I am going to calculate the standard deviation for both male and female school life expectancy. Standard deviation can be calculated using this formula: N represents the number of pieces of data.

In the table I got sigma X by adding all the data together... 17.1 + 10.9 + 4.9 (and so on) In the table I got sigma X squared by squaring all the data then finding the total... I calculated the standard deviation for females in exactly the same way and it was: 3.727851258 (rounded is 3.7) 5. I have drawn a graph (see graph paper), which represents and highlights how per capita GNP and average school life expectancy changes from country to country. This graph is a bar chart.

It is useful to me because it displays my data graphically. Graph two displays the school life expectancy for boys pictorially. Graph three displays the school life expectancy for girls pictorially. Graph four shows the average school life expectancy.

Interpretations and conclusions... Calculation one. I obtained a mean school life expectancy. This has proved very useful to me because it has allowed me to do other calculations, without this mean it would have been impossible for me to do such calculations. Having a mean has also allowed me to look at my data more generally instead of specifically at male and female school life expectancies, this means instead of two column (male and female) I can compare just one average column to the per capita GNP which is more effective as it means that better comparisons can be drawn between the two. I believe that a mean provides a more general representation of school life expectancy in countries around the world.

Calculation two. Finding the male and female school life expectancy means. This calculation has been useful to me because I can compare male and female school life expectancy more easily. Here I have rounded the figures to two decimal places. On average a male (any country) receives 12.28 years of education while a female (any country) receives an average of 12.33 years of education. These figures tell me that males and females receive very similar, almost the same amounts of education.

Females receive slightly more education (0.05 years) but the difference is so small it is almost none-existent. Calculation three. Finding the standard deviation for male and female school life expectancy. Standard deviation is a measure of dispersion and measures how far results are spread from the mean.

Standard deviation is considered to be "the most satisfactory measure of dispersion, since it makes use of all the scores in the distribution and is also quite acceptable mathematically". This is what I found the standard deviations to be (rounded figures): Male: 3.3 Female: 3.7 Once again there isn't a huge difference in the results that I have collected, which means there isn't a huge difference in the lengths of education males and females can expect to receive. However there is a small difference and this tells me that the amount of education females receive (in years) changes more from country to country than the amount of education (in years) that males receive. Therefore males can expect to receive a more uniform length of education wherever they are as opposed to females where the amount of education they receive changes more in each different country around the globe. Calculation five. I drew graphs to display my results.

I believe that my graphs display my results and data in a more exciting and easy to read manner. After analysing my graphs I can conclude that the general trend is that the higher the per capita GNP is the higher the school life expectancy is. This is a general trend displayed in the vast majority of the results but not in every single one. The graphs are also useful because they have allowed me to compare data for each country visually instead of just looking at the figures in a table. The general trend in other graphs is that females seem to receive marginally more education the males, however this is only by a small amount.

The graphs support conclusions I have made and my evaluation. Having done different calculations, looking at the results and analysing the data I can make conclusions and comparisons. When analysing some of my results I have used rounded figures, as they are easier to work with and easier to understand. I have compared male and female school life expectancies and found that although extremely similar females can expect to receive slightly more education than the average male.

I have also discovered that the length of education females receive changes more than the amount that males receive. I have been able to draw these conclusions by taking averages (means) of the data and calculating standard deviations. I have fully understood the statistical significance of the work I have done. Finding the rank correlation in calculation four showed me that per capita GNP and average school life expectancy are related and they seem to change together. If I draw my results from calculations four and five together I can say that they are related and the general trend is that as per capita GNP increases the average school life expectancy increases.

My investigation has limitations as I only looked at the data for twenty different countries and the figures that I used my not be as accurate as possible. The data I collected could change dramatically over the next decade or so as population increases so fast and this would mean that my investigation wouldn't be relevant and would be useless. I could improve my investigation by using a larger sample of data and working to a greater degree of accuracy.