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Quantitative Data Analysis

Below the introduction, the report provides a brief overview of the data used, including a statement on the adequacy, and the implications of this factor. Using the Statistical Package for the Social Sciences (SPSS), the study further explored specific features of the data used, including highlights on frequencies and descriptive statistics. Two extra variables (the total number of health conditions that a doctor ever told an ELSA respondent they have or have had and prevalence of disabilities that limit activities) were developed in SPSS and used for further analysis of the variations in heart conditions and correlation between income health statuses. Multivariate regression of depression scores and severity of disability was then performed as the last bit of analysis. A summary of the health statuses of the older people in England was provided just before the list of references that preceded the appendix (comprising syntax files obtained through the SPSS).The data used to compile this report was obtained from the English Longitudinal Study of Ageing (ELSA). ELSA is an interdisciplinary resource for data pertaining to health, economic wellbeing and quality of life as people in England age (The Institute for Fiscal Studies, 2011). The data collected usually represents persons aged 50 years and above. The Institute for Fiscal Studies explains that the sample from which the data is obtained is representative of the English population falling within the recommended age bracket. This implies that the organisation takes time to calculate a sample size that would be both financially viable to reach as well as one that is not too small to represent the qualities under investigation (Lavrakas, 2008). Additionally, the results obtained from the representative sample have the added advantage of increased ease of generalization to the entire population that it was obtained from.

Quantitative Data Analysis