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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

In Lesson 1 we introduce

- random variables
- the probability density function (PDF)
- the cumulative distribution function (CDF)
- the expected value, variance and standard deviation of a discrete random variable

Simply reading the content in this lesson will not be sufficient: students will need to complete a sufficient number of Exercises and WeBWorK problems in order to prepare themselves for the final exam.

source: http://wiki.ubc.ca/Science:MATH105_Probability/Lesson_1_DRV

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The content on the MATH 105 Probability Module by The University of British Columbia Mathematics Department has been released into the public domain. Anyone has the right to use this work for any purpose, without any conditions, unless such conditions are required by law.

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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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