In this week, we take a look at cross-tabulation or contingency tables, which deals with analysis of tabular data. This implies analysis of categorical/nominal variables. Moreover, chi-square and other measures of association are discussed, too.
Crosstabulation or contingency tables deals with analysis of tabular data, which implies analysis of categorical/nominal variables. In this module, chi-square and other measures of association are discussed.
Upon successful completion of this module, you will be able to:
- Develop research questions and testable hypotheses linked to existing theory or research.
- Develop hypotheses, choose appropriate statistics to test them, and describe the results correctly in a short research paper.
- Develop research questions and testable hypotheses linked to existing theory or research.
- Perform descriptive and inferential statistical analysis of public administrative datasets using IBM SPSS software.
- Interpret results from descriptive and inferential statistical analysis of public administrative datasets and place results in APA formatted text, tables, and figures.
Requirements: 3_4 | .doc file
Answer preview
Healthcare is a complicated sphere of practice considering that the existence of numerous disparities characterizes the society. Moreover, one must appreciate that these disparities affect people differently; hence people facing the same challenges may experience varied outcomes. As such, it is essential to examine data on a particular healthcare concept and determine the categories that one can utilize to gauge a specific phenomenon’s impact across multiple dimensions. The hypothesis is that age is a significant determinant of healthcare outcomes in any given society. Subsequently, the research questions are: How does age affect the incidence of lifestyle diseases like diabetes? And how does its occurrence vary across the broader spectrum of adulthood as one grows older?
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