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R Software to complete this task - Coursework Example

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That is, we determine whether the histogram is symmetrical (normally distributed) or skewed to one side or the other. From the histogram above, life…
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Unit: Statistical Methods for Engineering and Science (a) Histogram graphical display for the life expectancy across the 182 countries.The shape of the histogram above will help us explain the distribution of the life expectancy data point across the 182 countries. That is, we determine whether the histogram is symmetrical (normally distributed) or skewed to one side or the other. From the histogram above, life expectancy is negatively skewed. The 182 data points are sufficient enough to conclude that the distribution is negative skewed (-0.8175339).The reason for describing life expectancy as negatively skewed is because skewness can be measured numerically by calculating the third central limit (-0.8175339). The negative skewness implies that there are more data points on the left side of the histogram (negative side of a skew plot).

One can conclude that the life expectancy across the 182 countries is well below 70 years.(b) Scatter plot of Life expectancy against Internet users across the 182 countries.The scatter plot indicate that the data points are concentrated between internet users 0 to 20 for every 100 people. (c) The scatter plot above barely indicate any form of correlation between internet usage and life expectancy. However, it is clearly indicative that as internet usage increase from 20 to 80, the life expectancy tends to stay above 70 years and steadily moves towards 80 years.

This can be simply explained by the fact that increased internet usage leads to better health care awareness. Being exposed to better and healthy living habits and information through the internet may be the cause for increased longevity.(d) Histogram graphical display for the life expectancy across Europe.The histogram for life expectancy in Europe also shows that the distribution is negatively skewed, but much lesser compared to the entire world life expectancy. The skewness coefficient stands at (-0.52496). However, looking at the bar plots above, there seems to be a reduced number of age data points on the left side.

This means that Europe experience increased longevity compared to the world (Reimann et al.). A careful look at the histogram shows that between ages 60 to age 78, the distribution is symmetrical. However, when the age limit is extended above 80, the distribution becomes negatively skewed.(e) The scatter plot below shows the data points to less clustered. The data points are rather fairly distributed across the graph and shows that internet users across all ages seem be steady.(f) The life expectancy in Europe is much higher compared to the 182 countries.

The first histogram plot clearly shows that the life expectancy across the 182 countries is 70 years, while the second histogram plot shows that the life expectancy in Europe is at 78 years. Both histograms distribution are negatively skewed, however, Europe seems to have more access to information technology (internet access) which obviously has improved the living standard and heath care for the aging population. In addition, one can also conclude that since Europe has many developed markets, a huge proportion of the population is able to buy personal computers and also meet costs of accessing the internet (Reimann et al.).Work CitedReimann, Clemens, R Dutter, Robert Garrett, and Peter Filzmoser.

Statistical Data Analysis Explained: Applied Environmental Statistics with R. Hoboken, N.J: Wiley, 2013. Internet resource.

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