Sometimes it may feel tricky to find out what analysis method to choose for one’s study. Indeed, all the components influencing on the selection, such as research questions, types of data, measurement levels, observed distributions, etc., are entangled. However, there is certain logic behind the selection criteria.
It’s good to start with research questions: what do you want to know and can your data answer on that question? How variables and observed values could inform you about the questions asked?
The table below includes some of the most common analytical settings and their related procedures. The first colum asks what type of variables do you have, what is their measurement level? The second is about the association that is studies, whether it is a linear correlation, between-groups mean difference, or difference in joint frequencies. The third column lists some of the statistics that can be used and the fourth a suitable statistical test for testing whether the observed results are not likely to be by chance alone. The last column suggests a type of visualization for the results.
|Variables||Type of association||Descriptives||Statistical test||Visualization|
|Two continuous variables x and y||Linear correlation between x and y||Mean, median, standard deviation||Correlation coefficient & coefficient of determination||Scatter plot of x and y|
|Continuous y and categorical x||Differences in means of y between categories of x||Mean, median, standard devation||T-test, (ANOVA)||Box plot, mean plot|
|Two categorical variables x and y||Differences in joint categories of x across y||Mode, range, relative frequencies||Chi square||Contingency table of x and y, stacked bar chart|