# Statistical Testing for Various Research Questions

Modern data analysis includes multiple approaches allowing to conduct of tests for dependent and independent variables in different scenarios. Descriptive statistics, correlation, T-test, ANOVA, and regression can be applied to test healthcare researches information to provide exact responses to studied questions. For example, the answer to “What is the average age of participants in this study?” should be based on the one-sample t-test statistical analysis. The selected approach is suitable because age is an independent variable, and the participants’ nature can be identified as normal (UCLA Institute for Digital Research and Education [UCLA], 2021). The question “Did participants’ knowledge of increase after participating in the study?” requires the one-way ANOVA test. The analysis will show if the studied variable increased, decreased, or remained for the independent variables based on the interval changes of the dependent (UCLA, 2021). The choice for a statistical test requires assessing the variables and determining how research outcomes must be interpreted.

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If the study needs to clarify “What is the relationship between the number of days exercised per week and cardiovascular disease?”, data analysis should rely on multivariate multiple linear regression. That testing approach helps discover a relationship between various independent variables based on the dependent ones’ research outcomes (UCLA, 2021). To analyze the data that responds to the “What percent of participants are male?” question, the one-way MANOVA testing is suitable to apply. It includes analysis of independent variables for at least two dependent and can be applied to multiple groups simultaneously (UCLA, 2021). Statistical data analysis can also help determine changes and the dependence of one variable between numerous groups. For example, to answer the research question “Following participation in the study, is there a significant difference between the self-efficacy of group 1, group 2, and group 3?” the ordered logistic regression testing needs to be applied. Participants’ characteristics measured in each group are independent, and the analysis allows the parameters to determine the distinction (UCLA, 2021). The choice for appropriate testing for multiple groups should be based on the dependent variables’ nature.

## Reference

UCLA Institute for Digital Research and Education. (n.d.). Choosing the correct statistical test in SAS, STATA, SPSS, and R. Web.

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