Media Summary: Determining the probability density function of a function of a random variable using the CDF technique. My first whiteboard video! An example of how to determine the probability density function of a function of a random variable X. Lecture on the basic rules of counting with a few examples, indlucing the famous birthday problem.

Ma 381 Section 6 2 - Detailed Analysis & Overview

Determining the probability density function of a function of a random variable using the CDF technique. My first whiteboard video! An example of how to determine the probability density function of a function of a random variable X. Lecture on the basic rules of counting with a few examples, indlucing the famous birthday problem. One theorem and several worked out problems using counting principles. Lecture on the construction of the normal random variable and its probability density function. Also, an example of how the normal ... Definition of a moment generating function and how it is used to determine moments of a random variable.

A lecture on determining sample spaces and events given an experiment in probability. Example of what a conditional distribution is and how it is built. A discrete example of coin flipping is used. Definition of a conditional probability density function as well as an example. MIT 8.333 Statistical Mechanics I: Statistical Mechanics of Particles, Fall 2013 View the complete course: ... A lecture on determining if X and Y are independent random variables. We look at the joint density function and determine if it is ... A worked out example on the whiteboard of a joint density function.

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MA 381: Section 6.2: Functions of a Random Variable, Part 2
MA 381: Section 6.2: Functions of a Random Variable Example Worked Out at a Whiteboard
MA 381: Section 2.2: Counting Principles, Part 1
MA 381: Section 2.2: Counting Principles, Part 2
MA 381: Section 7.2: Normal Random Variable
MA 381: Section 11.1: Moment Generating Functions, Part 2
MA 381: Section 1.2: Sample Space and Events
MA 381: Section 8.3: Introduction to Conditional Distributions, Part 1
MA 381: Section 8.3: Conditional Probability Density Function for Continuous Random Variables
PSYCO 381 - Chapter 6 - Part 2
6. Probability Part 2
MA 381: Section 8.2: Independent Random Variables
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MA 381: Section 6.2: Functions of a Random Variable, Part 2

MA 381: Section 6.2: Functions of a Random Variable, Part 2

Determining the probability density function of a function of a random variable using the CDF technique.

MA 381: Section 6.2: Functions of a Random Variable Example Worked Out at a Whiteboard

MA 381: Section 6.2: Functions of a Random Variable Example Worked Out at a Whiteboard

My first whiteboard video! An example of how to determine the probability density function of a function of a random variable X.

MA 381: Section 2.2: Counting Principles, Part 1

MA 381: Section 2.2: Counting Principles, Part 1

Lecture on the basic rules of counting with a few examples, indlucing the famous birthday problem.

MA 381: Section 2.2: Counting Principles, Part 2

MA 381: Section 2.2: Counting Principles, Part 2

One theorem and several worked out problems using counting principles.

MA 381: Section 7.2: Normal Random Variable

MA 381: Section 7.2: Normal Random Variable

Lecture on the construction of the normal random variable and its probability density function. Also, an example of how the normal ...

MA 381: Section 11.1: Moment Generating Functions, Part 2

MA 381: Section 11.1: Moment Generating Functions, Part 2

Definition of a moment generating function and how it is used to determine moments of a random variable.

MA 381: Section 1.2: Sample Space and Events

MA 381: Section 1.2: Sample Space and Events

A lecture on determining sample spaces and events given an experiment in probability.

MA 381: Section 8.3: Introduction to Conditional Distributions, Part 1

MA 381: Section 8.3: Introduction to Conditional Distributions, Part 1

Example of what a conditional distribution is and how it is built. A discrete example of coin flipping is used.

MA 381: Section 8.3: Conditional Probability Density Function for Continuous Random Variables

MA 381: Section 8.3: Conditional Probability Density Function for Continuous Random Variables

Definition of a conditional probability density function as well as an example.

PSYCO 381 - Chapter 6 - Part 2

PSYCO 381 - Chapter 6 - Part 2

Today's lecture we're going to wrap up

6. Probability Part 2

6. Probability Part 2

MIT 8.333 Statistical Mechanics I: Statistical Mechanics of Particles, Fall 2013 View the complete course: ...

MA 381: Section 8.2: Independent Random Variables

MA 381: Section 8.2: Independent Random Variables

A lecture on determining if X and Y are independent random variables. We look at the joint density function and determine if it is ...

MA 381: Section 8.1: Joint Density Function - Whiteboard Quiz Example 2

MA 381: Section 8.1: Joint Density Function - Whiteboard Quiz Example 2

A worked out example on the whiteboard of a joint density function.