Mathematics and statics for economists - Statistics Project Example

The sample data for happiness is positively skewed which means that most people interviewed has a positive happiness level. The kurtosis of 15.41579212 shows that the probability of extreme values is less than for a level of happiness, and the values are wider spread around the mean of 4.820680628. The histogram gives a clear graphical representation of positive kurtosis and skewness. The data are concentrated to the left of the mean level of happiness representing a general positive level of happiness among the sample population.

In a nutshell, the data is positively skewed but with a median of 5, the data is almost normally distributed considering that the mean is 4.820680628. From the Anova results above, the P value 0.00 while the significance level α=0.05. The P value 0.00< α=0.05 hence we do not accept the null hypothesis that the mean level of happiness is significantly different from 5. This means at 95% confidence level, the mean level of happiness (4.547351) cannot be categorically stated to be different from 5.

If the mean is less than or more than 5, then it is statistically correct to state that it represents the sample mean. The correlation results show that level of happiness and means of traveling to work exhibit a positive association. The correlation coefficient is 0.819346. This happiness and means of travelling travel in the same direction. The regression equation shows the relationship between happiness and means of travelling travel in the same direction. According to the regression line, an increase of means of travelling to work by one unit will increase the level of happiness 2.

740298 when all factors are held constant. From the regression result, means of traveling to work positively influence the level of happiness. This means the two variables exhibit a positive relationship. The results according to the link above show that there effects of commuting to the level of happiness at