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WST 111 Practical 1

WST 111 Practical 1

Chapter 9 Exercises

Chapter 9 Exercises

Tutorial 4 part 2

Tutorial 4 part 2

Example 9.8 & Case 3 Intro

Example 9.8 & Case 3 Intro

Sections 9.1 & 9.2

Sections 9.1 & 9.2

Chapter 9- Introduction

Chapter 9- Introduction

Solutions to Chapter 5 exercises EXPLAINED

Solutions to Chapter 5 exercises EXPLAINED

Section 5.2 - Expected Values, Covariance, and Correlation

Section 5.2 - Expected Values, Covariance, and Correlation

Section 5.1 - Jointly Distributed Random Variables

Section 5.1 - Jointly Distributed Random Variables

Solutions to Gamma Excercises Explained

Solutions to Gamma Excercises Explained

Section 4.4 (Part 2) - Exponential distribution (Introduction and Application)

Section 4.4 (Part 2) - Exponential distribution (Introduction and Application)

Section 4.4 (Part 3) - Exponential distribution (Memoryless Property) & Chi-Squared Distribution

Section 4.4 (Part 3) - Exponential distribution (Memoryless Property) & Chi-Squared Distribution

Section 4.4 (Part 1) - Gamma distribution

Section 4.4 (Part 1) - Gamma distribution

Quiz 11 (Part B) Memo

Quiz 11 (Part B) Memo

Section 4.3 (Part 3) - Approximating a Discrete Distribution with a Normal Distribution

Section 4.3 (Part 3) - Approximating a Discrete Distribution with a Normal Distribution

Section 4.3 (Part 1) - Uniform & Normal distribution

Section 4.3 (Part 1) - Uniform & Normal distribution

Section 4.3 (Part 2) - Nonstandard Normal Distribution

Section 4.3 (Part 2) - Nonstandard Normal Distribution

Section 4.2 (Part 2) - Moment generating functions

Section 4.2 (Part 2) - Moment generating functions

Section 4.2 (Part 1) - Expected values

Section 4.2 (Part 1) - Expected values

Section 4.1 (Part 3) - Percentiles

Section 4.1 (Part 3) - Percentiles

Section 4.1 (Part 2) - CDFs

Section 4.1 (Part 2) - CDFs

Section 4.1 (Part 1) - Introduction & PDFs

Section 4.1 (Part 1) - Introduction & PDFs

Introduction to Integration

Introduction to Integration

Section 3.7 MGF and Poisson Process

Section 3.7 MGF and Poisson Process

Section 3.7 The Poisson Distribution

Section 3.7 The Poisson Distribution

Section 3.4 Moments and moment generating function Part 2

Section 3.4 Moments and moment generating function Part 2

Section 3.4 Moments and moment generating function Part 1

Section 3.4 Moments and moment generating function Part 1

Section 3.3 Variance of discrete rv

Section 3.3 Variance of discrete rv

Section 3.3 Expected values of discrete rv

Section 3.3 Expected values of discrete rv

Chapter 3.2 Examples on Cdf

Chapter 3.2 Examples on Cdf

Chapter 3.2 Probability distribution Cdf

Chapter 3.2 Probability distribution Cdf

Chapter 3.2 Examples on Pmf

Chapter 3.2 Examples on Pmf

Chapter 3.2 A parameter of a probability distribution

Chapter 3.2 A parameter of a probability distribution

Chapter 3.2 Probability distribution Pmf

Chapter 3.2 Probability distribution Pmf

Chapter 3.1 Random variables

Chapter 3.1 Random variables

Section 2.5- Independence (part 2)

Section 2.5- Independence (part 2)

Section 2.5- Independence (part 1)

Section 2.5- Independence (part 1)

Section 2.4- Conditional Probability (part 6)

Section 2.4- Conditional Probability (part 6)

Section 2.4- Conditional Probability (part 5)

Section 2.4- Conditional Probability (part 5)

Section 2.4- Conditional Probability (part 4)

Section 2.4- Conditional Probability (part 4)

Section 2.4- Conditional Probability (part 3)

Section 2.4- Conditional Probability (part 3)

Section 2.4- Conditional Probability (part 2)

Section 2.4- Conditional Probability (part 2)

Section 2.4- Conditional Probability (part 1)

Section 2.4- Conditional Probability (part 1)

Practical 2 Video (Part 1)

Practical 2 Video (Part 1)

Section 2.3- Counting techniques (part 4)

Section 2.3- Counting techniques (part 4)

Section 2.3- Counting techniques (part 3)

Section 2.3- Counting techniques (part 3)

Section 2.3- Counting techniques (part 2)

Section 2.3- Counting techniques (part 2)

Section 2.3- Counting techniques (part 1)

Section 2.3- Counting techniques (part 1)

Section 2.2- Axioms, interpretations and properties of probability (part 3)

Section 2.2- Axioms, interpretations and properties of probability (part 3)

Section 2.2- Axioms, interpretations and properties of probability (part 2)

Section 2.2- Axioms, interpretations and properties of probability (part 2)

Section 2.2- Axioms, interpretations and properties of probability (part 1)

Section 2.2- Axioms, interpretations and properties of probability (part 1)

Section 2.1- Sample spaces and events (part 4)

Section 2.1- Sample spaces and events (part 4)

Section 2.1- Sample spaces and events (part 3)

Section 2.1- Sample spaces and events (part 3)

Section 2.1- Sample spaces and events (part 2)

Section 2.1- Sample spaces and events (part 2)

Section 2.1- Sample spaces and events (part 1)

Section 2.1- Sample spaces and events (part 1)

Discussion of Memo for Section 1.3 & 1.4 Exercises

Discussion of Memo for Section 1.3 & 1.4 Exercises

Section 1.3 - Measures of Location

Section 1.3 - Measures of Location

Practical 1 Discussion Video

Practical 1 Discussion Video

Memo for Section 1.2 Exercises

Memo for Section 1.2 Exercises

Section 1.1 - Discussion & Memo

Section 1.1 - Discussion & Memo

Chapter 1 - Introduction and Overview

Chapter 1 - Introduction and Overview

Section 1.4 - Measures of Variability

Section 1.4 - Measures of Variability

Section 1.2 (Part 2) - Histograms

Section 1.2 (Part 2) - Histograms

Section 1.2 (Part 1) - Stem and Leaf Displays and Dotplots

Section 1.2 (Part 1) - Stem and Leaf Displays and Dotplots

Section 1.1 - Populations and Samples

Section 1.1 - Populations and Samples