# Statistics Essays

Poverty, which is measured by the household income lower than poverty line has been identified as the dependent variable in this project. It is important to know which elements are associated with poverty. The purpose of this paper is to evaluate the key determinants of American household poverty in 1980. The four possible determinants will be analyzed in this project, the average numbers of every family (FAMSIZE), URB is the percent of people live in urban, UR is the level of people have no job over 16 years and the median family income in US dollars (INCOME). Descriptive statistics, correlation and regression will be used in this project.

2. Descriptive statistics Variable | Mean | Median | Mode | VAR | STDEV |

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The correlation coefficient between poverty and URB = CORREL (C2:C59; G2:G59)= -0.0397(4 decimal places), see appendix. The correlation coefficient of -0.0397 means a slightly negative linear relationship between poverty and URB. The t statistics = -0.0397*SQRT ((58-2)/(1-(-0.0397)^2))= -0.297467. If try the significant level of 10% again, the t-crit (0.05, 58-2)= 1.672522, t-stat is still within the critical value. Hence, the null hypothesis for URB cannot be rejected, it is concluded that the URB effect is not statistically different from zero.

Using the same calculation method, between poverty and family size, the correlation coefficient = CORREL (D2: D59; G2: G59)= 0.2938, it means that there is a small positive relationship between poverty and FAMSIZE.

The t-stat = 0.2938*SQRT ((58-2)/(1-0.2938^2))= 2.300369, which is higher than t-crit, therefore reject the