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 life expectancy is high. The skew of the population is -1, which means the distribution is negative divergence compared to normal distribution.

Second, the descriptive analysis of developed sample obviously shows that the average life expectancy of developed countries is higher than the population. The maximum and minimum of developed countries respectively is 83 and 69, and the minimum of developed sample is equal to the mean of population, so it can be seen that the life expectancy of developed countries is obviously high. The mean and medium of developed sample respectively is 78 and 80, which also is high. In addition, the standard deviation of developed countries also is low, which means that the gap of the life expectancy of developed countries is not large.

Third, the descriptive analysis of developing countries show that the descriptive value of developing countries is closed to the whole sample, and the mean and medium is the same, which means the life expectancy of developing countries can represent the world. The results of developing sample also show that the life expectancy of some developing countries is extremely lower than the average expectancy.

Forth, the descriptive analysis of the least developed countries obviously shows that the life expectancy is lower than the developed countries. The mean of least developed sample is 57 and the medium of the least developed sample is 55, so it can be seen the life expectancy of least developed countries is extremely low. The skew of the least developed sample is 1, so the distribution is positive divergence.

In a word, the descriptive statistical analysis obviously shows that the life expectancy is closed with the economic development, and the life expectancy of developed countries is higher than the developing and least developed countries.

Coefficient of variability

The part respectively calculates the coefficient of variation of the several samples, so to make a comparison.

CV (population)