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Bayesian Simple linear regression/Evidence
Method evidence record

Bayesian Simple linear regression

Bayesian Simple Linear Regression models the relationship between a continuous outcome and a single predictor by combining a Gaussian likelihood with prior distributions over the intercept, slope, and error variance. The result is a full posterior distribution over all parameters, providing probabilistic uncertainty quantification rather than a single point estimate.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Bayesian Simple Linear Regression
Taxonomic method record · regression-model / statistics
  • Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. · ISBN 978-1439840955
  • McElreath, R. (2020). Statistical Rethinking: A Bayesian Course with Examples in R and Stan (2nd ed.). CRC Press. · ISBN 978-0367139919
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Claims persisted in the evidence ledger, each with its own assessment.

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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketBayesian Generalized Linear Modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian Multiple linear regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian Quantile Regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian Robust Regressionmachine-suggested · Relational suggestion, not evidence.Same method familyOLS Regressionmachine-suggested · Relational suggestion, not evidence.Same method familySimple Linear Regressionmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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