Analytical Methods in Economics and Finance - Assignment Example

this basis establishes similarity in life satisfaction among males and females. Consistency in other values such as standard deviation that was 1.67 for males and 1.71 for females, skewdness that was -1.31 for males and -1.27 for females, and range, minimum, and maximum values that were all similar for males and females supports the position that life satisfaction for both males and females assume the same trend. The following table summarizes descriptive statistics for life satisfaction based on gender (Weiers 2011, p. 58- 66). People with in income category 6 offered a higher mean life satisfaction score, 7.

84, as compared to people in income category 1 whose mean score was 7.79. The mean and the mode for the two categories was however at score eight to suggest similarity in distribution. With a standard deviation of 1.59 for category 1 and 1.53 for category 2, together with difference in minimum satisfaction value, 0 for category 1 and 3 for category 3, the mean appears the best estimator to suggest that people in income category 6 have higher life satisfaction score than people in category 1 (Healey 2009, p. 85- 125). The high significance value of F, 0.

79, relative to the test level of significance of 0.05, means that the null hypothesis is not rejected. This means that no significant relationship exists between life satisfaction, gender, and males and females are equivalently satisfied. The computed value is however higher and this means that the null hypothesis is not rejected. The regression coefficient is therefore zero and this shows that life satisfaction does not depend on gender and confirms the observation that the distribution of life satisfaction score, by gender is the same.

The p-value is however greater and the null hypothesis is not rejected. This means that there is no significant relationship between money (income