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Correlation between Development measures.

The indicators we use to measure development are useful in determining the level of development of places.  Generally, we would expect many of the indicators to be correlated together. The expression “correlated” means that they should link to one another and affect one another.  For example, in a country with high Gross National Product we would expect a high number of Internet users as the country has the money available for a high quality cable network.  Similarly, we might expect countries with Low Gross National Product to have high numbers of people per doctor as it is expensive to train and pay doctors, and to pay for the facilities they would require.

 

There are 2 examples below dealing with the following measures of development

·         Gross Domestic Product is the total market value of goods and services that a country produces in a year per person.  This is measured in US$.

·         Life Expectancy is the length of time the average person in a country can expect to live for.

·         Infant mortality is the number of babies who do not survive past the age of 1 year old for every 1000 live births in a population.

 

The graph reveals a POSITIVE correlation that is reasonably STRONG.  This is because the points are close to the line and as one variable goes up so does the other.  This means that as GDP goes up so does the average age a person can expect to live to.  This makes logical sense, in countries with high GDP such as the USA there are very good food distribution systems, clean water, education facilities and excellent medical care. All of these features maximize people’s chances of living a long and healthy life.  Sadly, in poorer countries such as Burkina Faso their lack of wealth and high levels of debt mean that they cannot afford the same things as the USA, resulting in a lower life expectancy.

The scatter graph above shows a NEGATIVE correlation between the 2 variables.  Here, we can see that as the GDP per capita (person) goes up, the infant mortality falls rapidly.  In Burkina Faso, a huge infant mortality of 81 infants under 1 dying before the age of 1 in every 1,000 live births is a tragedy. It is a reflection of their status as a Highly Indebted LDC, which cannot afford decent maternal care, vaccines and medical care for newborn infants.  This will not be the case in richer countries such as the UK and Japan.

 

Not all variables will be linked together in this way, but the majority will be, and there will always be countries that disrupt the trend.  However, when correlating data this way some distressing patterns emerge for the world’s poorest countries which have;

·         The highest infant mortalities

·         Shorter life expectancies

·         Lower calorie intake per person

·         Higher maternal death rates

·         Higher incidents of HIV, AIDS and Malaria

·         Lowest access to safe drinking water

·         The highest % of people undernourished

·         The lowest per capita incomes

·         The poorest literacy rates and shortest educations

This is where Aid and fairer trading can really make a difference to the poorest people in the world, who have been dubbed the “bottom billion”.

 

     
Think about it
Visit GapMinder and explore a range of graphs about development.

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