SOCSCI 2J03 Lecture 5: Stats 2J03 - Chapter 5

• School: McMaster University
• Department: Social Sciences
• Course: SOCSCI 2J03
• Professor: Rizwan Tahir

Document Summary

In all these examples, the number of customers, cars, and students are random; that is, each of these can assume any value within a certain interval. Types of variables: discrete variable assume countable values, continuous variable assume any value contained in one or more intervals. Discrete random variables: discrete random variable examples, make 100 sales calls (random variable # of sales) Probability distribution of a discrete random variable: the probability distribution of a discrete random variable is a graph, table, or formula that specifies the probability associated with each possible value the random variable can assume. Two characteristics of a probability distribution: 1. 0 p(x) 1 for each value of x. Example 2: using the probability distribution listed in table 5. 3 of example 1, find the following probabilities: (a) the probability that a randomly selected family owns two vehicles. = . 425 (b) the probability that a randomly selected family owns at least two vehicles.