![]() ![]() After preparing data for analysis, researchers then proceed with the actual statistical analysis and finally report and interpret the results.įamily medicine and community health researchers often limit their analyses to descriptive statistics-reporting frequencies, means and standard deviation (SD). Statistical analysis requires a series of steps beginning with formulating hypotheses and selecting appropriate statistical tests. Research hypotheses provide a proposition about the expected outcome of research that may be assessed using a variety of methodologies, while statistical hypotheses are specific statements about propositions that can only be tested statistically. Quantitative research involves collecting structured or closed-ended data, typically in the form of numbers, and analysing that numeric data to address research questions and test hypotheses. Investigators in family medicine and community health often employ quantitative research to address aims that examine trends, relationships among variables or comparisons of groups (Fetters, 2019, this issue). Researchers in family medicine and community health can follow specific steps to ensure a systematic and rigorous analysis. The following are the general steps for statistical analysis: (1) formulate a hypothesis, (2) select an appropriate statistical test, (3) conduct a power analysis, (4) prepare data for analysis, (5) start with descriptive statistics, (6) check assumptions of tests, (7) run the analysis, (8) examine the statistical model, (9) report the results and (10) evaluate threats to validity of the statistical analysis. After examining a brief overview of foundational statistical techniques, for example, differences between descriptive and inferential statistics, the article illustrates 10 steps in conducting statistical analysis with examples of each. It is aimed at individuals new to research with less familiarity with statistics, or anyone interested in reviewing basic statistics. The purpose of this article is to provide an accessible introduction to foundational statistical procedures and present the steps of data analysis to address research questions and meet standards for scientific rigour. ![]()
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