Data analysis guides, written the way results have to be reported
Ten pillar guides covering the software and the methods we use on client engagements — each with the formulas, assumption tests, worked examples and reporting templates that examiners and reviewers expect.
Choose a tool or a method
Every guide is self-contained: what the method does, what it assumes, how to run it, and how to report it.
SPSS Analysis: A Complete, Worked Guide for Research and Business Data
A professional SPSS analysis guide: data preparation, reliability testing, assumption checks, the exact menu paths for t-tests, ANOVA, correlation and regression, and how to report each result in APA format.
Read guide 12 min readR Analysis: A Reproducible Workflow for Statistical Research
How to run credible statistical analysis in R: project structure, tidyverse data cleaning, descriptive and inferential tests, diagnostics, model comparison and reproducible reporting with worked code.
Read guide 12 min readPython for Statistics: From Clean Data to Defensible Inference
Professional statistical analysis in Python: pandas cleaning, scipy hypothesis testing, statsmodels regression with full summary output, assumption diagnostics and when to use scikit-learn instead.
Read guide 13 min readRegression Analysis: Assumptions, Interpretation and Worked Examples
A rigorous guide to simple and multiple linear regression: the model, OLS estimation, the five assumptions, multicollinearity, interpreting β and R², and reporting results in APA format.
Read guide 12 min readANOVA: One-Way, Two-Way and Repeated Measures Explained
How analysis of variance works, when to use one-way, factorial and repeated measures ANOVA, the F-ratio and sums of squares, assumption tests, post hoc procedures and APA reporting.
Read guide 11 min readLogistic Regression: Odds Ratios, Assumptions and Model Fit Explained
How binary logistic regression works, how to read odds ratios and confidence intervals, the assumptions that actually apply, model fit statistics, classification accuracy and APA reporting.
Read guide 12 min readTime Series Analysis: Stationarity, ARIMA and Forecast Accuracy
A practical time series guide: decomposition, testing stationarity with ADF and KPSS, differencing, identifying ARIMA orders from ACF and PACF, seasonal models, diagnostics and forecast accuracy metrics.
Read guide 11 min readPanel Data Analysis: Fixed Effects, Random Effects and the Hausman Test
How to analyse panel data: pooled OLS versus fixed and random effects, what each estimator identifies, the Hausman test, clustered standard errors, and diagnostics for serial correlation and unit roots.
Read guide 12 min readSurvey Data Analysis: Cleaning, Weighting, Scales and Valid Inference
How to analyse survey data properly: cleaning and screening, handling missing responses, validity and reliability of scales, weighting and complex sample designs, choosing tests for Likert data, and reporting.
Read guide 12 min readAcademic Research Analysis: From Research Questions to Defensible Results
How to run and write up the data analysis chapter of a thesis or dissertation: aligning hypotheses with tests, assumption checking, effect sizes and power, APA results reporting, and the errors examiners catch.
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