Frequently Asked Questions
How do I choose the right statistical test?
Start with our Statistical Test Decision Tree. It walks you through a short series of questions about your research design: How many variables do you have? What type of data are they (categorical or continuous)? How many groups are you comparing? Based on your answers, it recommends a test and links you to the relevant tutorial. If you are still unsure after using the decision tree, talk to your methodology advisor — they can confirm the recommendation in the context of your specific study.
What is effect size and do I need to report it?
Effect size tells you how large a difference or relationship is, not just whether it is statistically significant. Most journals and the APA now expect you to report effect sizes alongside your p-values. Common measures include Cohen's d (for group comparisons), Pearson's r (for correlations), and eta-squared or partial eta-squared (for ANOVA). We have a full tutorial on effect size and a free Effect Size Calculator on Subthesis.
Is this site free?
Yes. Every tutorial, guide, cheat sheet, and tool on Stats for Scholars is free. The calculators on Subthesis are also free. There are no paywalls, no premium tiers, and no required sign-ups.
Can I use these tutorials for my dissertation?
Absolutely. The tutorials are designed with dissertation and thesis work in mind. That said, this site is an educational resource, not a citable primary source for statistical theory. Use it to learn the concepts, then cite the original methodological references (such as Cohen, 1988 for effect size or Field, 2018 for general statistics) in your dissertation.
Do you offer tutoring or consulting?
Stats for Scholars does not currently offer one-on-one tutoring or statistical consulting. The site is designed to be a self-service resource. If you need personalized help, we recommend your university's statistical consulting center, your dissertation committee or methodology advisor, or peer study groups in your program.
What software should I use for my analysis?
It depends on your field, your committee's expectations, and your comfort level. SPSS is widely used in education, psychology, and health sciences. R is free, open-source, and extremely powerful. Python (with libraries like scipy, statsmodels, and pingouin) is popular in data science and some research fields. Excel can handle basic analyses. If your program or advisor has a preference, follow their lead. See our software guides for step-by-step instructions.
How do I cite this site?
If you want to reference Stats for Scholars in a paper or presentation, you can use the following APA-style format: Reyes, A. (n.d.). Stats for Scholars. Retrieved [date], from https://statisticsforresearch.com. Remember that for your dissertation's literature review, you should cite the original statistical sources rather than a tutorial site.
I found an error — how do I report it?
We take accuracy seriously. If you spot a mistake — whether it is a typo, a formula error, or an explanation that could be clearer — please open an issue on our GitHub repository. Describe what you found and where you found it, and we will review and correct it as quickly as we can.
What is the difference between Stats for Scholars and Subthesis?
Stats for Scholars is the learning side: tutorials, concept explanations, cheat sheets, and guides. Subthesis is the computing side: free online calculators for effect size, power analysis, sample size, t-tests, ANOVA, chi-square, correlation, regression, and reliability. The two sites are designed to work together. Read a tutorial here, then run your numbers on Subthesis.
Do I need to know math to use this site?
No. The tutorials are written for researchers, not mathematicians. We explain concepts in plain language and use research examples instead of abstract formulas. Where formulas are shown, they are accompanied by step-by-step explanations of what each part means. If you passed your introductory research methods course, you have more than enough background to follow along.