Consumption of household comes from household Income, which accumulates to become the Income of other group people, and the money continues flowing.

Variables used ; Dependent Variable: Gross domestic product (GAP) Independent variables: Household final consumption expenditure. Data Points: 1990-2012 Data Source: https://data. Workloads. Org/Null Hypothesis: Ho: There is no relationship between Household final consumption and GAP Alternate Hypothesis: HI : There exists a relationship between Household final consumption and GAP Data set -Detailed analysis of various models Interpretation of the Results – As per the regression results, R square value for the cubic model is the highest, however we can see close R-square value for Log Linear, Quadratic and Linear model as well.

Hence we can say that this model explains the relationship between independent and dependent variables. As R square value is very high and, the significance value is nearly O which is less than 5% (taken as default), we can reject the null hypothesis stating that there is a relationship between the household institution expenditure and GAP.Considering the above two models It Is clear that ten cool model NAS a netter explanatory power. To establish a relationship between Adult mortality rate of a country and the various factors that can impact like Expenditure on health, price of cigarettes (most popular brand), number of people infected with HIVE and the percentage of population using sanitation facilities. A Priori – Higher government expenditure on health improves the health standards of the country and hence decreases the mortality rate.Cigarettes cause lung cancer and Geiger the price of cigarettes, more people would be De motivated thus decreasing consumption which in turn would drive down the mortality rate.

Better sanitation facilities decreases chances of death due to cholera and diarrhea. The number of HIVE infections in a country also determines the mortality rate Variables Used – Dependent Variable: Adult Mortality rate of a country (per 1000 population) Independent variables: Expenditure on health Most sold brand of cigarettes (price in SIS$) Population using improved sanitation facilities (%) Number of people living with HIVEData Points used: 2011 Data Source: https://www. Who. Into/research/en/ Null Hypothesis: Ho: There is no relationship between the adult mortality rate and the factors like Expenditure on health, price of cigarettes(most popular brand), number of people infected with HIVE and the percentage of population using sanitation facilities . HI : There exists a relationship between the adult mortality rate and the factors like infected with HIVE and the percentage of population using sanitation facilities .

Data set – Detailed Analysis – Additive Model Detailed Analysis – Multiplicative ModelIn the additive model the adjusted RE value is of 0. 762 and the significance level for the expenditure on health and the price of cigarettes is on the higher side. The variables expenditure on health and the price of cigarettes were also found to be highly correlated among themselves.

In the multiplicative model the adjusted RE values is of 0. 667. Here the significance level of the price of cigarettes was found to be on the higher side compared to others. Considering the above two models it is clear that the additive model has a better explanatory power.