Statistics & Data Analysis
Statistics for researchers, in plain English — descriptive statistics, hypothesis tests, correlation and regression, factor analysis, SEM, p-values and effect sizes — and how to choose and interpret the right test.
All Statistics & Data Analysis guides
15 articles
Convergent & Discriminant Validity: AVE, HTMT and Fornell-Larcker Thresholds
The exact thresholds examiners check: AVE ≥ 0.50, loadings ≥ 0.708, HTMT below 0.85/0.90, and the Fornell-Larcker criterion — what each means, and what to do when a construct fails.
How to Interpret SmartPLS Bootstrapping Results (t-Values, p-Values, CIs)
You've run bootstrapping in SmartPLS — now what do the t-values, p-values and confidence intervals actually mean? A path-by-path reading guide, with the reporting format reviewers expect.
How to Choose the Right Statistical Test: A Decision Guide
Every statistical test answers three questions: what are you testing, how many groups, and what type of data? Answer those and the right test chooses itself — here's the complete decision map.
How to Analyse Likert Scale Data in SPSS (Without Getting It Wrong)
Mean or median? Parametric or not? Item vs summated scale? The practical, defensible way to analyse Likert data in SPSS — the workflow, the tests and the classic examiner objections.
Mediation vs Moderation Analysis: What They Mean and How to Run Them
Mediators explain *how* an effect happens; moderators explain *when* it's stronger or weaker. Plain-English definitions, how to test each (PROCESS, AMOS, SmartPLS), and how to report them.
What Is Jamovi? The Free SPSS Alternative, Honestly Reviewed
Jamovi is free, open-source statistics software with an SPSS-like interface built on R. What it does well, where it can replace SPSS for a thesis, and where it can't.
What is Meta-Analysis? Pooling Evidence the Right Way
Meta-analysis pools effect sizes from many studies into one weighted estimate. The core concepts — effect sizes, fixed vs random effects, heterogeneity, forest and funnel plots — explained without the algebra.
Model Fit Indices in AMOS Explained (CFI, RMSEA, CMIN/df & More)
CMIN/df, CFI, TLI, RMSEA, SRMR — what each fit index actually measures, the thresholds examiners expect, and what to do (and not do) when your model doesn't fit.
How to Use SPSS for Thesis Analysis: A Practical Roadmap
From raw questionnaires to reportable results: the seven-step SPSS workflow every thesis analysis follows — data entry, cleaning, reliability, descriptives, testing and reporting.
What is SmartPLS? PLS-SEM Explained for Thesis Research
SmartPLS runs PLS-SEM — the variance-based cousin of structural equation modelling. What it is, when it's the right choice, and the full analysis workflow with the thresholds reviewers check.
SPSS vs R vs Python: Which Should You Learn for Your Research?
Point-and-click ease, statistical depth or full flexibility? A practical comparison of SPSS, R and Python to help you pick the right tool for your thesis.
Reliability and Validity Explained (With Examples)
If your measures aren't reliable and valid, your results mean nothing. A plain-English guide to both — and how to report them in your thesis.
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Frequently asked
How do I choose the right statistical test?+
Three questions decide it: what type of data do you have (categorical/continuous), how many groups or variables are involved, and what are you testing — difference, relationship or prediction? Answer those and the test usually chooses itself.
What matters more — p-value or effect size?+
Both, together. The p-value says whether an effect is likely real; the effect size says whether it is big enough to matter. Journals and examiners increasingly expect effect sizes and confidence intervals alongside significance.
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