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# Evaluating Descriptive statistical Results

To evaluate the dataset, a statistical descriptive approach has been taken, in which, kurtosis, mean and standard deviation has been calculated for both developed and under-developed countries. Which, in turn, would help us to determine the relevance of the dataset, the values calculated are illustrated below for both variables.

 Developed Mean 1078.494458 Standard Error 32.9977345 Median 1077.704228 Standard Deviation 246.9324341 Sample Variance 60975.627 Kurtosis -1.264159751 Skewness 0.016532853 Range 813.3111293 Minimum 678.2458178 Maximum 1491.556947 Sum 60395.68964 Count 56 Largest(1) 1491.556947 Smallest(1) 678.2458178 Confidence Level (95.0%) 66.12893768

It can be determined that the mean value calculated for developed countries amount to 1078, which represented the average value of the entire population in developed countries. Furthermore, the standard deviation amounted to 246.93, which represented the difference between the distance of the mean value and its outliers. Moreover, the kurtosis calculated for amount to a negative 1.24, which represented that the distribution was light tailed and the probability that the next generated would be low, was high.

 Underdeveloped Mean 1272.485658 Standard Error 49.3343984 Median 1255.957043 Standard Deviation 369.1848324 Sample Variance 136297.4405 Kurtosis -1.249668996 Skewness 0.0880224 Range 1211.462867 Minimum 700.5497113 Maximum 1912.012578 Sum 71259.19686 Count 56 Largest(1) 1912.012578 Smallest(1) 700.5497113 Confidence Level (95.0%) 98.86834376

It can be determined that the mean value calculated for under-developed countries amount to 1272, which was more than the mean value calculated for developed countries. However, which represented the average value of the entire population in under-developed countries. Furthermore, the standard deviation amounted to 369, which represented the difference between the distance of the mean value and its outliers. Moreover, the kurtosis calculated for amount to a negative 1.24, which represented that the distribution was light tailed and the probability that the next generated would be low, was high.

# Conclusion

After analyzing the dataset, regarding the worldwide population with respect to developed and under-developed countries. Therefore, it can be concluded that the population growth in underdeveloped countries was more densely populated than developed countries. Which can be determined from our analysis conducted above, where the average population of under-developed countries was more than the developed countries. However, it can also be evaluated from the dataset collected and later sorted, in which, the yearly population of under-developed countries was more than developed countries each years. Whereas, the both type of population represent an increasing trend, where they both increased from the year 1960 to 2015.

# Top-downDecision-Tree Formulation

The tree above represents the population of under-developed countries, where the size of the tree is 11 with a Root Squared error amounting to 48.79%

The tree above represents the population of developed countries, where the size of the tree is 11 with a Root Squared error amounting to 48.79%.

# Evaluating Descriptive statistical Results

To evaluate the dataset, a statistical descriptive approach has been taken, in which, kurtosis, mean and standard deviation has been calculated for both developed and under-developed countries. Which, in turn, would help us to determine the relevance of the dataset, the values calculated are illustrated below for both variables…………………….

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