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# Random Variables - AP Stats Chapter 16

Part 1

by

Tweet## Steve Mays

on 3 December 2012#### Transcript of Random Variables - AP Stats Chapter 16

Random Variables - part 1 AP Stats Chapter 16 In this chapter we are going to look at Random Variables and their distributions.

There are two types of random variables: Discrete and Contiuous. Discrete Random Variables are variables that can be counted, like the number of siblings, or the number of cars that go through a drive through, or how many times you win a game at Kings Island. Continuous Random Variables are variables that can be measured, like your height, or the amount of water in a cup, or the time it takes you to drive to school. In part 1, we will focus on Discrete Random Variables. What is a probability model or probability distribution? The mean of a probability distribution can also be called, "The Expected Value" of a probability distribution. The formula for the expected value (mean) and standard deviation of a probability distribution for a discrete random variable are . . . Here's another example of working with a probability distribution. In the next lecture, we will look at what happens if you combine the parameters of two or more probability distributions. Just for fun. See you in stats class. . .

Full transcriptThere are two types of random variables: Discrete and Contiuous. Discrete Random Variables are variables that can be counted, like the number of siblings, or the number of cars that go through a drive through, or how many times you win a game at Kings Island. Continuous Random Variables are variables that can be measured, like your height, or the amount of water in a cup, or the time it takes you to drive to school. In part 1, we will focus on Discrete Random Variables. What is a probability model or probability distribution? The mean of a probability distribution can also be called, "The Expected Value" of a probability distribution. The formula for the expected value (mean) and standard deviation of a probability distribution for a discrete random variable are . . . Here's another example of working with a probability distribution. In the next lecture, we will look at what happens if you combine the parameters of two or more probability distributions. Just for fun. See you in stats class. . .