Lecture 01: Review on
probability
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Lecture 02: Graphical models
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Lecture 03: Discrete-time
Markov chain - Part I
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Lecture 04: Discrete-time
Markov chain - Part II
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Lecture 05: Review on
statistical inference
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Lecture 06: Inference on Markov
chain
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Lecture 07: Monte Carlo
methods
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Accessible HTML is generated by converting the PDF to HTML via pandoc. Gemini AI wrote a simple script for me to run this conversion. See this page for introduction.
To help you study, I have set up a custom NotebookLM AI Study Assistant for this course. This tool is an interactive AI trained strictly on our STAT 516 lecture notes.
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How to use it: You can ask the AI to explain difficult proofs, compare notation across lectures, or generate conceptual practice questions based on our class materials.
⚠️ Important Disclaimer: Generative AI models can occasionally misinterpret algebra or “hallucinate” mathematical properties. Always verify the AI’s derivations against the official lecture notes above.
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