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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