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1
Julia: Useful tidbits
2
Random sampling with rand
3
Several random objects
4
Uniform sampling
5
Tossing a weighted coin
6
Bar charts and histograms
7
Probability densities
8
Rolling multiple dice
9
Converging shape
10
Normalising the y -axis
11
Options for plotting functions
12
Normalising the x axis
Description:
Explore sampling and random variables in this 56-minute lecture from MIT's Computational Thinking Spring course. Dive into Julia programming language concepts, starting with useful tidbits and progressing through random sampling techniques. Learn about uniform sampling, weighted coin tossing, and creating bar charts and histograms. Investigate probability densities, simulate rolling multiple dice, and observe converging shapes. Discover methods for normalizing axes and explore various options for plotting functions. Gain practical insights into computational thinking and statistical concepts using Julia throughout this comprehensive lecture.

Sampling and Random Variables in Julia - Lecture 9

The Julia Programming Language
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