Probability and statistics

Justin SALEZ C7

Justin SALEZ C6

Justin SALEZ C4

Justin SALEZ C1

StatMech-03: Cumulative Distribution and Functions of Random Variables

What the Area Under a Normal Distribution REALLY Means

The art and science of uncertainty - with David Spiegelhalter

Bounded Differences Inequality (aka Azuma-Hoeffding Inequality)

Hypothesis Testing

Chebyshev inequality (Eitan)

Markov's Inequality (Eitan)

UofM - MATH 2740 - Lecture 11 - Part 1 - PCA (theory, continued)

UofM - MATH 2740 - Lecture 10 - PCA (theory)

UofM - MATH 2740 - Lecture 05 - Part 2 - Fitting Canada census

A pretty reason why Gaussian + Gaussian = Gaussian

Estimation d'un paramètre

Estimating a parameter

But what is the Central Limit Theorem?

Cours 12 - Hétérogénéité de groupe et spatiale

Cours 12 - Hétérogénéité de groupe et spatiale

Cours 11 - Quelques curiosités et modèles en plus

Cours 11 - Quelques curiosités et modèles en plus

Régression logistique. 1 ) Principe

Logistic Regression. 1) Principle

Régression logistique. 2) Pratique

Logistic Regression. 2) Practical Application

Bayes' theorem

Multi-Dimensional Gaussian Probability Density Functions

Learning About Quantum States 6: Central Limit Theorems and more for the RSK process on random words

UofM - MATH 2740 - Lecture 12 - Part 1 - PCA (computer example 2)

UofM - MATH 2740 - Lecture 11 - Part 3 - PCA (computer example 1)

Properties of expectation and variance

Use of Bernoulli variable to empirically estimate a distribution

Empirical distribution

GG ChiSquared Overview

REVISION LESSON 4 ON SCALES OR LEVELS OF MEASUREMENT: NOMINAL || ORDINAL || INTERVAL || RATIO.

LESSON 50 - CHOOSING THE RIGHT STATISTICAL TESTS: FACTORS TO CONSIDER WHEN CHOOSING A TEST

LESSON 48 - INFERENTIAL STATISTICS: MEANING & USE OF HYPOTHESES IN INFERENTIAL STATISTICS

LESSON 47 - DESCRIPTIVE STATISTICS: THE THREE METHODS OF ANALYSING DATA DESCRIPTIVELY

LESSON 46 - DATA ANALYSIS: BASIC CONCEPTS IN DATA ANALYSIS || TYPES OF STATISTICS & STATISTICAL TEST

LESSON 32 - STRATIFIED RANDOM SAMPLING: DEFINITION & STEPS OF CONDUCTING STRATIFIED RANDOM SAMPLING

LESSON 30 - SAMPLING: RANDOM/ PROBABILITY SAMPLING TECHNIQUE & GENERATION OF RANDOM NUMBERS

LESSON 28 - SAMPLING: DEFINITION OF TERMS USED IN SAMPLING, PURPOSE & LIMITATIONS OF SAMPLING

LESSON 5- CLASSIFICATION OF VARIABLES AND SCALES OF MEASUREMENT (NOMINAL, ORDINAL, INTERVAL, RATIO)

Écart type

Standard deviation