Assignment Purpose
The Literature Review is often the very first stage of any research project and it provides a backbone and context for all
Introduction –
What is human development?
The concept is defined as how we can create a greater expand the amount freedom and opportunities people have by simple improving their well-being. Whether or not certain locations take the opportunity to make use of these improvements can help us decide if the area is developed or not.
Human development also continues to expand throughout our daily lives as we make different choices to better or worse our future.
Variables:
The variables being studied here are amount of Physicians and Total Health Expenditures. The amount of physicians will be measured at rate per 10,000 people from 2003-2012. Meanwhile, the health care expenditures are taken as the percentage of GDP in 2011. Various other factors are going to correlate to the data and directly affect the numbers due to a countries location such as national income, quality of education, and unemployment rate. I expect to see less physicians in areas that spend less on healthcare due to the less amount of people being able to afford paying for the medical system.
Analysis –
Total Healthcare expenditures:
This is the amount of public and private healthcare expenditure added together, which covers health services, family planning, nutrition, and emergency aid. Does not include supply of sanitation or water.
GDP (Gross Domestic Product): How Healthcare is being measured:
The value of all goods and services within a nation’s borders over set period of time?
Physicians:
Defined as a person qualified to practice medicine. The MedicineNet specifies this by any person who has earned their “Doctor of Medicine (MD), Doctor of Osteopathy (DO), or Doctor of Naturopathy (ND) and is accepted as a practitioner of medicine under the laws of the state, province, and/or nation in which he or she practices.”
Hypothesis:
If a country has greater amount of healthcare expenditure, than the amount of physicians will be greater. Because of this this I believe the graph will be skewed to the right because with lower healthcare comes higher healthcare rates same would be applied for amount of physicians. The data would also be positively correlated because if there is a higher amount of healthcare, than there will most likely be more physicians in the area.
Total Health Care Expenditures:
Mean | 6.9 |
Median | 6.405580487 |
Std. Dev. | 3.1 |
Five Number Summary | |
Minimum | 1.646302863 |
Q1 | 4.858598619 |
Q2 | 6.405580487 |
Q3 | 8.701793937 |
Maximum | 19.48166465 |
Outlier Detection | |
IQR | 3.8 |
Lower Fence | -0.9 |
Upper Fence | 14.5 |
Lower Outliers | 0 |
Upper Outliers | 5 |
From the histogram, we can tell that Total Health Expenditures is skewed to the right. This means that there is a heavier concentration of countries on the left side of the graph with lower health expenditures. The skew of the graph is then further supported by the mean (6.9% of GDP) and median (6.4% of GDP) as the median has a lesser value than the mean. The minimum % of GDP is South Sudan with 1.64 while the highest is Liberia with 19.48, which gives us a pretty big range.
Amount of Physicians:
Mean | 15.2 |
Median | 10.9 |
Std. Dev. | 14.9 |
Five Number Summary | |
Minimum | 0.08 |
Q1 | 1.955 |
Q2 | 10.9 |
Q3 | 27.275 |
Maximum | 70.56 |
Outlier Detection | |
IQR | 25.3 |
Lower Fence | -36.0 |
Upper Fence | 65.3 |
Lower Outliers | 0 |
Upper Outliers | 2 |
From the histogram, we can tell that the amount of physicians is skewed to the right. There is a heavier concentration of countries on the left side of the graph with higher amounts of physicians. The skew of the graph is then further supported by the mean (15.2 physicians per 10,000 people) and median (10.9 physicians per 10,000 people) as the median has a lesser value than the mean. The minimum amount of physicians is Tanzania with .08 while the highest is Monaco with 70.56 physicians per 10,000 people.
Correlation:
The graph provided above allows us to depict that there is a negative correlation between the variables Amount of Physicians and Total Health Expenditures. People were able to spend less on their health in areas with more doctors because they may be more developed, which means they also offered better healthcare in the country. There are a few outliers in this graph such as the point Japan with coordinates (5, 17.85). This country holds the highest amount of physicians out of all the other countries. The data also seems to have a moderately strong correlation as the data points seem to be spread out from the regression line. The r-value in statistics typically ranges from -1.0 to +1.0. As r gets closer to either of these values, it depicts how much more closely related the variables are related. R in this scenario is .436875. Because it is positive it means as one variable gets larger or smaller the other variable will follow.
Analysis for Europe and Central Asia:
Health Expenditures:
Mean | 8.0 |
Median | 7.7 |
Std. Dev. | 2.1 |
Five Number Summary | |
Minimum | 3.9 |
Q1 | 6.275594031 |
Q2 | 7.7 |
Q3 | 9.4 |
Maximum | 12 |
Outlier Detection | |
IQR | 3.1 |
Lower Fence | 1.6 |
Upper Fence | 14.1 |
Lower Outliers | 0 |
Upper Outliers | 0 |
From the histogram there doesn’t seem to have a particular skew to the distribution of total health expenditures in Europe and Central Asia. There is a heavier concentration of countries on the left side of the graph with lower health expenditures as the mean and median prove that the date is skewed to the right. The mean is (8.0% of GDP) and median (7.7% of GDP) as the median has a lesser value than the mean. The minimum % of GDP is Mauritius with 3.9% while the highest is Sweden with 12%.
Physicians:
Mean | 31.0 |
Median | 33.4 |
Std. Dev. | 11.7 |
Five Number Summary | |
Minimum | 8.3 |
Q1 | 25.4 |
Q2 | 33.4 |
Q3 | 37.6 |
Maximum | 70.6 |
Outlier Detection | |
IQR | 12.2 |
Lower Fence | 7.1 |
Upper Fence | 55.9 |
Lower Outliers | 0 |
Upper Outliers | 1 |
From the histogram we can tell that the amount of physicians is close to being a normal curve. However, from the mean and median we can tell that the graph is actually skewed left. There is a heavier concentration of countries on the right side of the graph with higher amounts of physicians. The skew of the graph is then further supported by the mean (15.2 physicians per 10,000 people) and median (10.9 physicians per 10,000 people) as the median has a lesser value than the mean. The minimum amount of physicians is Tanzania with .08 while the highest is Monaco with 70.56 physicians per 10,000 people.
Correlation:
One this graph for Amount of Physicians versus Total Health Expenditures for Europe and Central Asia, there is a positive correlation between the two variables. There seems to be no outliers. However, the correlation still seems to be moderately strong according to the graph as the data points lie spread out from the regression line. The r-value in this scenario is .19055 which is positive which means the independent and dependent variables are correlated and as one variable grows the other variable will also grow.
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Assignment Purpose
The Literature Review is often the very first stage of any research project and it provides a backbone and context for all
Reading Analysis
Universal Methods 07 Bodystorming
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