Testing of Hypotheses-Specific Models
Introduction In this note, we shall discuss Designing statistical tests for hypotheses on parameters involved in some standard distribution. This
Frequentist, YES
Frequentist, YES
Testing of Hypotheses – Preliminaries
Introduction From a classical text, Mood, A. M., Graybill, F. A., & Boes, D. C. Introduction to the Theory of
Frequentist, YES
Point Estimation 3-Evaluation of Estimator
Introduction This notes confines to one of the ways of analyzing the quality of a point estimator for a parameter
Frequentist, YES
Point Estimation 2 – ML
Introduction This notes confines to MLE in obtaining Point Estimators for parameters Suggested Reading: [CABE] Casella, G., & Berger, R.
Frequentist, YES
Point Estimation 1 – MoM
Introduction This notes confines to MOM in obtaining Point Estimators for parameters Suggested Reading: [CABE] Casella, G., & Berger, R.
Frequentist, YES
Statistical Inference Preliminaries
Introduction This notes provides few ideas of sampling distribution of sample mean and variance Suggested Reading: [CABE] Casella, G., &
Bayesian, YES
Sequential Updating
Bayesian Tool Kit In Bayesian analysis, sequential updating refers to the process of continuously updating beliefs about a parameter as
Bayesian, YES
Normal Models – Two Parameters Case
Normal Model: Both $\mu$ and $\sigma^2$ are unknown In the one-parameter models, only $\mu$ or only $\sigma^2$ is unknown, so
SAS, SEE
Conjugate Bayesian Models SAS
This page presents SAS code for implementing Bayesian conjugate models using standard prior–likelihood formulations and their associated posterior distributions. For
Python, SEE
Conjugate Bayesian Models Python
This page presents Python code for implementing Bayesian conjugate models using standard prior–likelihood formulations and their associated posterior distributions. For