Week 6: Continuous Random Variables

Practical Skills: Advanced R Programming

Slides

Continuous Random Variables

• Continuous Random Variables
• Continuous parametric distributions

Advanced R Programming

• Functional programming
• Designing a simple simulation study

Performance Outcomes

You should feel confident to perform the following outcomes:

Continuous random variables

• Define and identify continuous random variables
• Distinguish between discrete and continuous random variables
• Interpret the probability density function (pdf) and cumulative distribution function (cdf) to calculate probabilities
• Apply properties of common continuous distributions (such as the Normal distribution)
• Solve problems involving continuous random variables in applied contexts
• Calculate expected values and variances for continuous random variables
• Use R to compute probabilities and summary statistics for continuous random variables
• Use R to generate random data, plot distributions, and compute probabilities and summary statistics for continuous random variables

Resources

If you don’t feel yet confident after going through the teaching materials or would like further resources, then you are also encouraged to go through the following materials.

• R for Data Science (2nd Edition)
  • Chapter 11: Communication
• OpenIntro Statistics (4th Edition)
  • Chapter 4.1: Normal distribution
  • Chapter 4.3.2: Normal approximation to the binomial distribution
  • Chapter 4.3.3: The normal approximatoin breaks down on small intervals

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