نصائح بحثية يومية

Freeze the analysis dataset once analysis starts. If new data arrive, version the dataset and rerun everything rather than patching numbers by hand.

Understand what adjusting for a variable does before adding it to a model. Adjusting for a mediator that lies on the causal path can hide the effect you want to measure.

When events are rare or cells are sparse, ask about exact methods instead of large-sample approximations. Standard chi-square tests behave badly with very small counts.

Learn one statistical package properly, whether R, SPSS, Stata, or another, and script the analysis so it can be rerun from raw data to final tables in one pass.

Plot the data before testing anything. A histogram and a scatterplot reveal outliers, skew, and coding errors that summary statistics hide.

Prespecify subgroup analyses and keep them few. Subgroups chosen after seeing the data are hypothesis-generating at best and misleading at worst.

Correlation says nothing about direction or cause. When you need relationships adjusted for other variables, that is a regression question, not a correlation question.