Real per capita income is among the values that indicate financial position of countries and people who contribute to their success. As it follows from the information presented in the report of the World Bank, twenty richest countries in the world (based on incomes per capita) include European countries, Asian countries, and countries in North America and Oceania.
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When it comes to research, there are two primary types of data; the latter can be quantitative or qualitative. The data that indicates the real incomes per capita for the richest countries in the world is quantitative. Unlike qualitative data, quantitative data can be quantified, and it usually refers to objective information whereas qualitative data can describe perceptions and opinions. Also, quantitative data can be used to provide a statistical feedback.
The range of data on twenty richest countries in the world in terms of incomes per capita is extremely large. As of 2016, the country with the highest income per capita is Monaco. Its income per capita in 2016 exceeds $180,000 (“Average income around the world,” 2016, para. 4). As for the twentieth member of the group, it is the United Kingdom. The income per capita of the latter is more than $42,000. As is clear from the exact numbers provided in the report, the data set has a range of 143,69.
The range is enormous as it exceeds the income per capita of all countries from the list except for Monaco. Considering that such a great difference exists between countries that are ranked among the richest in the world, it is quite hard to imagine the difference in the quality of life of citizens in the richest and the poorest countries in the world.
There are three main measures that are used all over the world to characterize numerical data: the average, the median, and the mode (“Averages,” n.d.). The average can be found if the sum of values is divided by the number of values. In the case under consideration, the average for the data set is 64,990. If the number of values is even, the median presents the midpoint of two numbers in the middle of a numerical series where “observations are sorted in the ascending order” (Leys, Ley, Klein, Bernard, & Licata, 2013, p. 765).
The chosen data set has a median of 54,525. The mode for the data set is based on the presence duplicate values. The mode for the given data is 43,660. The median and the average are quite close in values, and this is why it can be said that the data is normally distributed. In fact, there are situations when the average and the median are the same, but it usually occurs when there are a few numbers in a sequence of numbers. The same values of the median and the average indicate the perfect situation. In the given case, the distribution of the data is normal.
The variance of any data set indicates the degree to which data is spread out. The variance for the given data set is 1147,13; the standard deviation is the square root of the latter (Al-Saleh & Yousif, 2016). The standard deviation for the data set is 33,86. All countries included in the data set are different in terms of the relationships between their incomes per capita and the average for the data set. Thus, five countries from the list have a real income per capita that is greater than the average for the data set. At the same time, there are two countries in the 10% part of the range.
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Al-Saleh, M. F., & Yousif, A. E. (2016). Properties of the standard deviation that are rarely mentioned in classrooms. Austrian Journal of Statistics, 38(3), 193-202.
Average income around the world. (2016). Web.
Averages. (n.d.). Web.
Leys, C., Ley, C., Klein, O., Bernard, P., & Licata, L. (2013). Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median. Journal of Experimental Social Psychology, 49(4), 764-766.