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Reference and Selective Reading

The reading guide maps topics to tasks and evidence. This page distinguishes book indexes from exact external references so generated chapter boundaries do not mislead you.

Local book backbone​

  • Introduction to Probability: use the contents or search for sample spaces, counting, conditional probability, Bayes, random variables, distributions, expectation, covariance, densities, and limit theorems.
  • Mathematics for Computer Science: use the probability portion for alternate proofs and probability-versus-confidence reasoning.

The generated chunks are navigation artifacts, not a promise that one chunk equals one textbook section. Earlier guide links reused one chapter destination for unrelated section labels; this module now uses honest book-level links and explicit topic assignments. Full-book reading is not required.

Exact supplementary destinations​

Course-owned material​

Worked examples, practice solutions, assessment key, and the lab package are maintained with this module. Separate attempts from solutions when collecting independent evidence. If a source and a lesson disagree, report the precise claim and assumptions instead of silently choosing the answer that matches your calculation.