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Data

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Introduction
Statistical analysis is extremely essential for the data analysis, which mainly is used to for examining the internal relationship among the variables. The statistical analysis includes the data descriptive analysis, hypothesis test, regression analysis and others. The descriptive analysis mainly refers to calculate the mean, median, standard deviation, skew and other indicators. T or Z hypothesis test of means or proportions can be used for examining whether the distribution can be explained by the value. The regression analysis mainly aims to research the correlations of the variables, so to find calculate the coefficients of the variables and obtain the final equation (Gorlden, 1936). Therefore, the report mainly makes the data analysis of the life expectancy of the samples, so to find some internal relationship of the data.

Data analysis
Part 1: Statistical analysis
Descriptive statistical analysis
In order to conduct the descriptive statistical analysis of the life expectancy, the report mainly divides the population into three parts: developed countries, developing countries and least developed countries, so to calculate the descriptive statistical values. Based on the comparison of the three samples, it is appropriate to find the influence of the expectancy by the economic development. Table1: Descriptive statistical analysis of the sample

Sample | Minimum | Maximum| Mean| Medium| Standard Deviation | Skew | Population | 47| 83| 69| 73| 11| -1|
Developed| 69| 83| 78| 80| 4| -1|
Developing| 48| 79| 69| 73| 8| -1|
Least developed| 47| 74| 57| 55| 9| 1|

It can be found some basic discipline of expectancy by the descriptive statistical analysis. First, the maximum of the life expectancy of the population is Japan, and the minimum of the life expectancy is Central Africa Republic and Lesotho. The mean and medium of the population respectively is 69 and 73, and it can be seen that the average...