Bayesian Statistics — what's your goal?

Pick a category, then choose the specific analysis. All tests support Bayes Factors, ROPE, and multi-chain MCMC.

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Import a file, paste CSV, or try a demo dataset

Compare Groups

Test whether group means differ — t-tests, ANOVA, repeated measures.

Start with t-test

Categorical & Proportions

Independence in contingency tables, Beta-Binomial posterior for π.

Start with Contingency

Relationships & Prediction

Correlation BF, Bayesian regression (BIC + g-prior), and model averaging.

Start with Correlation

Advanced & Diagnostics

Sequential BF, posterior checks, BF robustness, meta-analysis, prior sensitivity.

Start with Sequential BF

Import / Paste / Demo Data

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Drag & drop a CSV / TSV file here

or click to browse (.csv .tsv .txt)

or paste below

Demo Datasets

Bayesian t-test

JZS Bayes Factor with Cauchy prior (Rouder et al., 2009). Supports: one-sample, independent, paired.

✓ Multi-Chain MCMC — 4 independent MH chains from over-dispersed starts. R̂ is true between-chain (Gelman et al. 2013). Set seed + chain count above. For publication, cross-verify with R BayesFactor.

Settings

Test Type

Variable 1

Variable 2

Test Value (μ₀)

Prior Width (r)

MCMC Chains

Random Seed (blank = auto)

ROPE Test

Bayesian One-Way ANOVA

BF10 for overall model with posterior means comparison.

Settings

Dependent Variable (numeric)

Independent Variable (groups)

Prior Width (r)

Bayesian Correlation

BF for Pearson correlation using stretched beta prior (Ly et al., 2016).

Settings

Variable X

Variable Y

Kappa (κ)

ROPE Test

Bayesian Contingency Tables

BF for independence test with posterior log-odds for 2×2 tables.

Table Input

Rows

Columns

Prior Concentration (a)

Bayesian Proportion Test

Beta-Binomial conjugate posterior. Savage-Dickey BF for H₀: θ = θ₀ (Wagenmakers et al., 2010).

Settings

Successes (k)

Trials (n)

H₀: θ₀

Prior α

Prior β

Bayesian Two-Way ANOVA

Multiplicative BFs for main effects and interaction (Rouder et al., 2017).

Settings

Dependent Variable

Factor A (groups)

Factor B (groups)

Prior Width (r)

Sequential Bayes Factor

BF trajectory as n grows. Optional stopping boundaries (Schönbrodt et al., 2017).

Settings

Variable

Test Type

Variable 2 (corr only)

Prior Width (r)

Upper Boundary (H₁)

Lower Boundary (H₀)

Bayesian Regression

BIC-approximated BF₁₀ + g-prior posterior β (Liang et al., 2008).

Settings

Outcome (Y)

Predictors (select multiple)

g-prior scale

Enable BMA (exhaustive)

Bayesian Model Averaging

Exhaustive 2^k model enumeration, BIC weights, inclusion probabilities.

Settings

Outcome (Y)

Predictors (select multiple, max 10)

Posterior Predictive Check

1000 replications, PPP-values for mean, SD, skewness, kurtosis.

Settings

Variable

Model

Replications

Seed

Bayesian Repeated-Measures ANOVA

BF₁₀ via JZS F-to-BF on within-subjects F.

Settings

Outcome (Y)

Subject ID

Time / Condition

Prior Width (r)

Bayesian Meta-Analysis

DerSimonian-Laird RE + BIC-approximated BF₁₀.

Effect sizes & SEs (paste CSV: d, se)

Prior Width (r)

BF Robustness Plot

BF₁₀ across prior parameter grid.

Settings

Based on

Prior Family

Prior Sensitivity Analysis

Robustness check of Bayes Factor across multiple prior widths and families.

Sensitivity Settings

Test Type

Prior Family

r range: 0.10 → 2.00