Next: Discrete Random Variables

Next: Discrete Random Variables

A Set of Open Resources for MATH 105 at UBC

- Home
- About
- Discrete Random Variables
- Continuous Random Variables
- 2.1 – The Cumulative Distribution Function
- 2.2 – A Simple Example
- 2.3 – The Probability Density Function
- 2.4 – A Simple PDF Example
- 2.5 – Some Common Continuous Distributions
- 2.6 – The Normal Distribution
- 2.7 – A Geometric Problem
- 2.8 – Expected Value, Variance, Standard Deviation
- 2.9 – Example
- 2.10 – Lesson 2 Summary

- Additional Problems

Next: Discrete Random Variables

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Next: Discrete Random Variables

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### Poll

**What is the most difficult concept to understand in probability?***How to calculate a PDF when give a cumulative distribution function. (59%, 303 Votes)*- In MATH 105, there are no difficult topics on probability. (17%, 87 Votes)
- What a random variableĀ is. (14%, 70 Votes)
- The difference between discrete and continuous random variables. (11%, 55 Votes)

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### Acronyms

Throughout this website, the following acronyms are used.

PDF = probability distribution function

CDF = cumulative distribution function

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