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Statistics
Bayesian Statistics
1. Foundations of Bayesian Inference
2. Single-Parameter Models
3. Multi-Parameter Models
4. Bayesian Computation
5. MCMC Algorithms
6. Hierarchical Models
7. Model Checking and Selection
8. Bayesian Regression Models
9. Advanced Topics
Single-Parameter Models
Introduction to Conjugacy
Definition of a Conjugate Prior
Mathematical Definition
Exponential Family Connections
Examples of Conjugate Pairs
Computational Advantages
Analytical Posterior Forms
Simplification of Calculations
Closed-Form Solutions
Limitations of Conjugacy
Restrictive Prior Choices
Real-World Applicability
Common Conjugate Families
Beta-Binomial Model
Model Structure
Beta Prior Distribution
Binomial Likelihood
Posterior Beta Distribution
Modeling Proportions
Example Applications
Parameter Interpretation
Gamma-Poisson Model
Model Structure
Gamma Prior Distribution
Poisson Likelihood
Posterior Gamma Distribution
Modeling Count Data
Rate Parameter Inference
Example Applications
Normal-Normal Model
Model Structure
Normal Prior Distribution
Normal Likelihood with Known Variance
Posterior Normal Distribution
Modeling Means
Precision and Variance Parameterization
Example Applications
Gamma-Exponential Model
Model Structure
Gamma Prior Distribution
Exponential Likelihood
Posterior Gamma Distribution
Modeling Rates and Lifetimes
Example Applications
Inverse-Gamma-Normal Model
Model Structure for Variance
Inverse-Gamma Prior
Normal Likelihood with Unknown Variance
Posterior Inverse-Gamma Distribution
Summarizing the Posterior Distribution
Point Estimates
Posterior Mean
Calculation and Interpretation
Optimality Properties
Posterior Median
Calculation and Interpretation
Robustness Properties
Posterior Mode
Maximum a Posteriori Estimation
Calculation and Interpretation
Relationship to Maximum Likelihood
Interval Estimates
Credible Intervals
Definition and Interpretation
Probability Statements
Highest Posterior Density Intervals
Definition and Calculation
Shortest Intervals
Equal-Tailed Intervals
Definition and Calculation
Symmetric Intervals
Comparison to Confidence Intervals
Differences from Frequentist Intervals
Interpretation Advantages
Practical Implications
Posterior Uncertainty Quantification
Posterior Variance
Posterior Standard Deviation
Coefficient of Variation
Posterior Predictive Distribution
Predicting New Observations
Definition and Purpose
Calculation Methods
Integration over Posterior
Averaging over Posterior Uncertainty
Parameter Uncertainty Propagation
Implications for Prediction
Prediction Intervals
Model Checking with Predictive Distribution
Posterior Predictive Checks
Discrepancy Measures
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1. Foundations of Bayesian Inference
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3. Multi-Parameter Models