# 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¶

Gilbert Strang lectures on linear algebra get vocal acclaim from the former students, as a kind of course that helped students gain a lot of confidence in the subject.

See also:

Computational Linear Algebra repository from

*fast.ai*.

## Calculus¶

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:

or as an nicely designed web page.

Authors recommend Khan Academy differential calculus course as a starter, but it is not a single downloadable reference.

*fast.ai* also has a calculus intro,
going rather quickly from one-arg function derivatives to deep learning.

## Probability and statistics¶

Probability and Statistics Cookbook (PSC), concise reference

Introduction to Probability by Charles M. Grinstead and J. Laurie Snell

An Introduction to Probability Theory and its Applications (Volume 1) by William Feller

See also:

5 must-haves for any #Probability library:

— Harry Crane (@HarryDCrane) January 10, 2020

Technical: Feller-Volume 1

Classic: Kolmogorov-Foundations of Prob

Real world: Taleb-Antifragile @nntaleb

Application: Grosjean-Exhibit CAA (alt. Jacobson-AAP)

Bio: Thorp-Man for all Mkts

What did I miss? RT/reply w your 5

## Numerical computing¶

## Other¶

140 unsorted formulas with a bit of Portugese, nice for a bulk review. Prepared by Rubens Zimbres.