How to choose an appropriate statistical analysis method?

Choosing an appropriate statistical analysis method involves selecting a technique aligned with your research question and data characteristics to yield valid and interpretable results. This decision is fundamental to robust scientific inquiry. Key considerations include the nature of your research objectives (description, comparison, relationship, prediction), the scale of measurement of your variables (nominal, ordinal, interval, ratio), the data distribution (e.g., normality), sample size and independence, and whether assumptions of specific tests are met. For instance, comparing means between two groups typically uses a t-test if assumptions hold, while analyzing relationships often employs correlation or regression. Carefully evaluate these factors before method selection. Begin by precisely defining the research question and hypotheses. Next, examine the data structure: identify dependent and independent variables, their measurement levels, distribution, and potential dependencies. Then, match these characteristics to suitable statistical techniques, considering parametric vs. non-parametric options if assumptions are violated. Finally, implement the chosen method and validate results through significance testing, effect size calculation, and residual analysis where applicable.