STAT 100 Lecture Notes - Lecture 9: Random Variable, Fair Coin, Sample Space

• School: University of Maryland
• Department: Statistics and Probability
• Course: STAT 100
• Professor: Cremins

Document Summary

Descriptions of chance behavior contain two parts: a list of possible outcomes and a probability for each outcome. A probability model describes the possible outcomes of a chance process and the likelihood that those outcomes will occur. A probability with a nite sample space is called nite. The probability distribution of a random variable x tells us what values x can take and how to assign probabilities to those values. Example: consider tossing a fair coin 3 times. De ne x = the number of heads obtained. The discrete probability model of a discrete random variable x relates the values of x with their corresponding probabilities. (discrete probability distribution) The distribution/model could be: in the form of a table, in the form of a graph, in the form of a mathematical formula. If x is a discrete random variable and x is a possible value for x, then we write p(x=x) as the probability that x is equal to x.