Data Analysis for UK General Household Survey

Introduction: Data Analysis for UK General Household Survey

Data Analysis for UK General Household Survey : Social capital is a function of an individual’s social group and interactions. Social capital develops through interpersonal relationships, having shared values and identities and networking with individuals and organizations. Social capital has been used as a measure of people’s success in entrepreneurship, supply chain and community evolution. Social capital is an important component used in explaining how cultures interact, trust and cooperate with one another in a country (Hoogendoorn 281). Besides, it is helps in estimating the level of economic viability of a region. According to King, Barbara, et al., the trust and honest between people in a nation determines the nation’s economic growth and wellbeing (125). The study explored the dynamics and determinants of the social capital and reported that the key determinants included trust, formal networking and norms, the institutional trust.

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The dual weighting scheme was introduced to the General Household Survey in 2000 and this would help in understanding of the various implications of the social capital weight among the populations. United Kingdom defines social capital in terms of the operational definition which include the networks, shared values, groups and shared norms. The purpose of this study is to explore the relationship between the social capital and level of education, the family structures and marital status.

The hypothesis in this study will include:

H1: There is no difference between the parents with independent children and parents with dependent children in terms of social capital.

H3: The social capital changes with an individual’s marital status.

H4: The level of appreciation of the social capital increases with the level of education

Data and Method: Data Analysis for UK General Household Survey

The data in this study consisted of the social capital elements from the UK General Household Survey. The survey usually focus on the various social capital elements including health, employment and income. Social Capital element of the UK General Household Survey consisting of 87 variables and 8221 cases were used. The study used secondary data considering that a large number of samples were involved. Furthermore, the survey is conducted periodically to help in the government planning in the United States. The dependent variable in the study was social capital while the independent variables were the marital status, level of education and household compositions. The dependent variable was operationalized to social capital weight in the study. The marital status was also postulated to be a significant determinant in the social capital computation; therefore, the participants were asked to state whether they were married, cohabiting, widowed or divorced. Under the level of education, the participants stated whether they were graduates or not. Finally, under household composition, one was expected to state the number of people in a family and whether they had kids or not. The variable also analysed whether the participant came from a single parent family.

In analysing the relationship between the dependent and independent variables, independent t-statistic test and linear regression analysis were used where appropriate. The analysis would help determine the difference among the variables subgroups in a variable of interest.

Results

The first hypothesis was that household composition affects the social capital index. The t-test statistics was conducted to determine whether the social capital index varied with the participants’ household composition. The results shows that parents with one dependent kid have a lower level of social capital index compared to parents with one independent kids. The null hypothesis is rejected because the p-value 0.53 is greater than critical value, p=0.05. There is a significant difference in social capital index between the parents with independent kids and those with dependent kids.

 

Group Statistics
  household type N Mean Std. Deviation Std. Error Mean
social capital weight lone parent with dep kids 618 3908.2730 1719.74898 69.17845
lone parent with indep kids 188 6797.8973 2164.59444 157.86927

 

The second hypothesis was that social capital index changes with the marital status. An independent t-test was conducted to determine whether the social capital index among the married differs from the social index among the unmarried.

 

Group Statistics
  marital status – dvmardf grouped N Mean Std. Deviation Std. Error Mean
social capital weight married 3801 6300.2605 1717.96669 27.86543
single 1766 5975.1597 3768.81983 89.68298

 

The results indicated that there is insignificant difference between the single and the married in terms of social capital index. Therefore, the null hypothesis is accepted since p=0.00 is lower than the critical alpha value, p=0.05.

Subsequently, the study also explored the role of education in the social capital index. The results indicated that people with higher education had a higher social capital index compared to those with other qualifications.

 

Group Statistics
  Education Level – 2000 (3 groups) N Mean Std. Deviation Std. Error Mean
social capital weight HIGHER EDUCAT 2015 5635.6946 2236.87233 49.83147
OTHER QUAL 2826 6013.2625 2793.18436 52.54284

 

Conclusion

The findings in the experiment are consistent with the hypothesis defined this research except for the marital status. The results indicates that there is no significant difference between the married and singles in terms of social capital index. On the other hand, level of education and household composition have significant role when determining the social capital value.

Works Cited

Hoogendoorn, Brigitte. “The prevalence and determinants of social entrepreneurship at the macro level.” Journal of Small Business Management 54.sup1 (2016): 278-296.

King, Barbara, et al. “Navigating shades of social capital and trust to leverage opportunities for rural innovation.” Journal of rural studies 68 (2019): 123-134.

Data Analysis for UK General Household SurveyData Analysis for UK General Household SurveyData Analysis for UK General Household Survey

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