You will learn how to:

- use a probability density function that may be defined as a piecewise function
- use the general result E\left( g\left( x \right) \right) =\int { f\left( x \right) g\left( x \right) dx }, where f\left( x \right) is the probability density function of the continuous random variable X, and g\left( x \right) is a function of X
- understand and use the relationship between the probability density function (PDF) and the cumulative distribution function (CDF), and use either to evaluate probabilities or percentiles
- use cumulative distribution functions of related variables in simple cases.

**Textbook**:

Cambridge International AS and A-Level Further Mathematics by McKelvey L., & Crozier M. (*Download eBook*)*Other Resources:*

List of formulae and Statistical Tables (List MF19) [Download]

**Technical Guide:**

Take note of the following…

1. Most videos are hosted on Youtube. For the best learning experience, follow the guidelines on this page “Tech Guide for students“.

2. Lessons are in succession. Thus, **Lesson 1 must be completed before you can have access to Lesson 2, Lesson 2 must be completed before Lesson 3, etc.** When you finish a lesson, you must click on the “** Mark Complete**” button at the bottom of the page.

### Course Instructor

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### Intro

### Probability Density Function (PDF)

### Cumulative Distribution Function (CDF)

### Expected values and Variances for Continuous Random Variables

### Finding the PDF and CDF of Y = h(X)

### REVIEW

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