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When measuring the progression of a country we use a term called development; this can be defined as a process of economic and social advancement in terms of quality of human life. It can be measured in terms of culture, wealth, education, healthcare,etc. by different indicators, single or composite. This report is based on the development Ethiopia, a country located in the Horn of Africa, as shown in the map (world atlas). It’s population is approximately 102 million inhabitants, making it the second most populous nation in Africa, and one of the poorest, with a GDP per capita of $783. Ethiopia’s main challenges in development are improving it’s economic growth and poverty reduction, which requires progress in job creation and improved governance. Other challenges are in the health and education ambit.
Looking at these challenges, GNI per capita(PPP,USD$) and infant mortality are the indicators that Ethiopia needs the most help with. GNI per capita (PPP,USD$) is the total value of domestic and foreign goods and services produced by a country’s residents in a given year divided by the total population and Infant mortality is the number of children dying under one year of age. Hypothesis: It is predicted that as GNI/capita increases, infant mortality will decrease because once Ethiopia increases its economy, more attention will be based on health care and making sure rural areas have the support they need meaning that infant mortality will decrease.
Data was collected for Ethiopia for the past 25 years (1990 to 2015) using Indexmundi for GNI per capita (PPP USD$) and Gapminder for life expectancy. These numbers were processed using a scatter plot, correlation coefficient and correlation line or line of best fit. Scatter plots were used because they show the relationship between two variables, in this case GNI per capita, (PPP USD$) and Life expectancy. To help know correlated the data is, a line of best fit was used; this was measured with the R-squared which helped identify whether the correlation was weak or strong.
Data was collected for GNI per capita (PPP,USD$) and infant mortality for east africa in 2015. As some countries in the region didn’t present recent numbers on these two indicators, countries with the most recent data were selected for this report. The data was processed using two statistical tools: scatter plot and line of best fit.
As shown in the graph above, starting from 1992 to 2001 there isn’t a correlation but from 2002 to 2016 it can be seen a slight negative correlation since the GNI per capita, (PPP, USD$) increased while life expectancy decreased The reason behind why there wasn’t a correlation from 1992 to 2001 was because Ethiopia had been in war with Eritrea from May 1998 to June 2000. The two most poorest countries spent hundreds of millions of dollars on the war and caused approximately 80,000 deaths according to BBC news (13 June 2016). Another reason was the Famine caused by drought that Ethiopia had to go through, the worst however was in 1984-1985, seven million people were suffering from starvation, as the report on BBC news made by Michael Buerk 1984 says “workers here say that this is the closest thing to hell on earth”, “death is all around, a child or an adult dies every twenty minutes”, “7. 000 now most apparently are dying of malnutrition, pneumonia and the diseases that prey on the starving”.
After this report the world was moved and organizations such as Save the Children, Live Aid and countries such as Britain, Poland, Germany, Canada and the United States intervened helping with donations and doctors.
Also the UN had been helping with aid programs and supplying better life saving operations in cases of droughts ever since. This has helped Ethiopia have less infant mortality since the major famine. Infant mortality started to decrease because there were improvements in the coverage of interventions for child survival in rural areas between 2000 and 2001. Tetanus toxoid, DPT3 and measles vaccination and oral rehydration solution (ORS) were provided to those who most needed it. That is why, as shown in the graph above, there was a decrease in infant mortality between 2000 to 2015, also the economy had major progress between these two time periods, this is because the government started to invest in infrastructure and foreign investors started to become more interested in Ethiopia.
Not only was Ethiopia affected by major droughts but all the surrounding countries suffered from hunger, making the infant mortality worse. As shown in Figure 4, it can be seen that the cluster was mainly countries bordering Ethiopia and the outliers are the ones that are further away. Seeing the regional data, it is clear that Ethiopia has less infant mortality compared to other countries in the region. Even though there isn’t a correlation according to the R-squared which is -0. 13, outliers can be seen. Mozambique is the country with the highest GNI per capita, (PPP, USD$) but it is also has high infant mortality. Somalia is the country with the least GNI per capita, (PPP, USD$) but also has infant mortality of 85. Mauritius and Seychelles have high GNI per capita compared to the other countries in the region and they also have the lowest infant mortality.
In conclusion, The original hypothesis for this report was proven wrong to an extent since in the regional nor the local data has a correlation and the R-Value is under 0. But nevertheless in the local data (figure 1) a slight negative correlation can be seen going from 2002 to 2015. Ethiopia’s economy is slowly improving with new investments made into the industrial world but health care and droughts are still major problems that the government has to improve. As shown in figure 4, other African countries are also dealing with improving their economy and infant mortality.
Ethiopia’s economy is slowly improving with new investments in the industrial sector but the reduction of Infant mortality needs to be done by several ways, in the case of Ethiopia, the government should place part of its investments into keeping the agriculture exportations strong and also find an alternative solution for droughts by using alternative drought tolerant crops like foxtail millet. With this, children will be able to have better nutrition and the parents will be more economically stable to be able to provide health care. Another way is to invest in local doctors and medicine. As stated in paediatrics, 70% of children are dying because of illnesses such as pneumonia, malaria, diarrhea, measles, HIV/AIDS and malnutrition.
The data collection method was reliable since it was collected from gapminder and Indexmundi which are used internationally for diverse studies. Even though it is reliable, the data may not be completely accurate. The use of r and r-squared was appropriate since it showed the relationship between the two variables and how correlated they were. Not enough data was collected to create a reliable test, as there were only 16 data points in the regional graph and 26 for the local whereas more data points given, the results are going to be better.
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