statistical tools for data analysis in research

Which approach to pursue depends on these practical issues: 1. These are all issues I take into account with my statistical consulting clients. This article outlines 5 practical issues to consider in choosing an analysis when you have options. The reality is that statistics is filled with grey areas, and there is often good justification for using a variety of statistical approaches to answer the same research question with the same set of variables.

I am not advocating data fishing or ignoring real issues like assumptions. One is numerical and therefore can be included in a relatively simple model, like a linear model, and the other is ordered categories and will need a more sophisticated model like a logistic regression. So you will nearly always still be left with options.įor example, it may be that two different dependent variables both answer your research question well, but require different analyses because they are measured on different scales. If you have not already, read about these in more detail.Īnswering those four questions well will often give you a range of statistical analyses that could all give you accurate results. Are there any data issues? (missing, censored, truncated, etc.) What is the Design? (between subjects, within subjects, etc.)Ĥ.

What is the scale of measurement of the variables used to answer the research question?ģ. There are 4 questions you must answer to choose an appropriate statistical analysis.Ģ.

Statistical tools for data analysis in research