Mathematic preliminaries

Typical prerequisites for statistics and econometrics are:

  • linear algebra

  • calculus

  • probability

They usually take 2-4 semester in college. Linear algebra is fully covered by VMLS, and Gilbert Strang lectures are highly recommended. Probability is exposed in PSC, even though it is a compact reference, not formally a textbook. Scipy lectures are a great one-stop resource for numerical computing basics.

Linear Algebra

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I do not have a one single source to recommend for calculus yet. Maybe it is a basic subject with no reason for a new basic textbook to appear in.

However, renewed interest for differentiation problems cames from deep learning subject area. The Matrix Calculus You Need For Deep Learning by Terence Parr and Jeremy Howard is a prime resource for matrix calculus, it is accessble as:

Authors recommend Khan Academy differential calculus course as a starter, but it is not a single downloadable reference. also has a calculus intro, going rather quickly from one-arg function derivatives to deep learning.

Probability and statistics

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