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Restaurants and Happiness/Life Satisfaction - Statistics Project Example

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For any human, satisfaction towards food is an crucial question and issue. Does a man get proper food? Is it with right nutritional value? Is it caters to his satisfaction and worthwhile of money he paid. Above all, does he get satisfaction ultimately both physically and mentally…
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Restaurants and Happiness/Life Satisfaction
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"Restaurants and Happiness/Life Satisfaction"

Download file to see previous pages The locations of the restaurant are identified in undeveloped countries and used to determine whether individual life satisfaction in given regions which increases or decreases across parallel income brackets. Independent variables were identified from the World Value Survey of individuals living in undeveloped countries to measure happiness/life satisfaction. This cluster of variables which are called subjective utility variables in this study, were used to support the Life Satisfaction score as it relates to happiness. The fixed effects OLS model is used as control for the number of restaurants in each region, to test the impact whether there is a restaurant or not in a region and to determine the effect of additional the restaurants on individual life satisfaction and happiness. For the purpose of this research, the relationship between the LIFE SATISFACTION score and the data associated with 12-15 subjective utility variables from the World Value Survey were considered. The data which was collected from the Internet was put to perform regression analysis to find out whether there exist some relationship between number of restaurants, mean life satisfaction and number of individuals. Table 6 shows that there is a weak correlation between these three variables which is depicted in the correlation matrix therein. Hence it is assumed that there exists no herteroscedasticity present. So the regression equation which represents the dependent variable as mean life satisfaction by keeping number of restaurants. ...
Heteroscedasticity is expected to affect the actual regression which is otherwise a plausible measure. Here, the first data set is the number of Restaurants locations in developing countries. This data was obtained from country specific Restaurants International websites. To determine which of the 54 countries in the CVS study should be included, developing country was based on the definition from the World Bank’s Atlas: a developing country is one whose per capital gross national income (GNI) is $12,195 or less (World Bank, 2009). This resulted in 35 countries (a total of 384 regions within these countries) meeting criteria for inclusion in this study. The survey involved 77,000 respondents with 58,770 respondents living within those developing countries (CVS, 2009). The data included only countries identified in the WVS study as a developing country. The total number of Restaurants in each region and city listed in the WVS study were carefully counted from each website and reflects an accounting for all open and running locations in January 2011. Since data set is to include the construction of new Restaurants locations takes on the store number of the previous, shut down locations, it was difficult to obtain an exact number of locations for the data set used in this analysis. Therefore, by reading archived newspaper articles many locations that opened or closed since 2008 were identified and the numbers adjusted accordingly. Then, the results for the WVS study for each region of each developing country was paired with the total number of Restaurants locations in each region. As Table 2 shows, of the 35 developing countries, Ghana, Burkina, Ethiopia, Mali, Rwanda, Zambia, and Iran have ...Download file to see next pagesRead More
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