The Statistical Test Selection Workbook: 58 Practical Decision Trees, Assumption Checklists, and Output Interpretation Templates for SPSS, JASP, and R - Paperback

by Rafiq Muhammad (Author)

Stop Guessing Which Statistical Test to Use. Start Analyzing with Confidence.

"Which test do I use?" It is the single most common question asked by graduate students and clinical researchers. You buy expensive, 800-page statistics textbooks that teach the advanced math. You watch endless tutorials that teach you where to click. Yet, when you sit down with your specific research question and your specific dataset, you are left completely paralyzed.

The Statistical Test Selection Workbook is the bridge between theoretical statistics and practical research application. This is not another textbook full of dense formulas. It is a strictly practical, fill-in-the-blank roadmap designed to take you from a raw research question to a publication-ready APA results paragraph.

Whether you are a doctoral candidate preparing for graduation or a clinical researcher conducting an inferential study, this workbook removes the anxiety of quantitative analysis. It guarantees that you select the methodologically correct test, verify the exact assumptions required, and interpret the software output flawlessly.

Inside this large-format workbook, you will find:

The Master Decision Tree - A multi-page, visual flowchart that walks you through "How many groups?" → "How many DVs?" → "What measurement level?" leading you to the exact statistical test you need.

Variable Classification Worksheets - Eliminate confusion by mapping out the precise types and roles (IV, DV, covariate, moderator) for every variable in your study.

Assumption Testing Checklists - Step-by-step diagnostic worksheets for normality (Shapiro-Wilk, Q-Q plots), homogeneity of variance (Levene's), linearity, and multicollinearity.

Output Decoder & Interpretation Templates - Annotated guides for SPSS, JASP, and R showing you exactly which numbers to report for t-tests, ANOVAs, regressions, chi-squares, and their non-parametric alternatives.

Effect Size & Power Worksheets - Simplified templates for calculating Cohen's d, eta-squared, odds ratios, and completing G*Power sample size planning.

APA 7th Edition Results Templates - Fill-in-the-blank paragraphs ensuring your final write-up meets strict academic and peer-review publication standards.

The Non-Parametric Emergency Guide - A parallel decision tree showing you exactly what to do when your data fails standard parametric assumptions.

Don't let statistical anxiety delay your dissertation or stall your research. Stop worrying about what your committee or peer reviewers will flag. Secure your methodology, run your tests with confidence, and publish your results.