ITM 107 Lecture Notes - Lecture 12: Sample Space, Fair Coin, Empirical Probability

• School: Ryerson University
• Department: Information Technology Management
• Course: ITM 107
• Professor: Aziz Guergachi

Document Summary

Lecture 9 introduction to probability: when we toss coin, it can land in one of two ways, heads or tails. Each sample point in the sample space is assigned a nonnegative probability measure or probability weight such that the sum of the weights in the sample space is 1. We can usually construct more than one sample space for an experiment: the sample space in which each sample point is equally likely is called an equiprobable sample space. Suppose the number of elements in a sample space is n(s) = n, with each element representing an equally likely outcome of a probability experiment. Then the weight (probability) assigned to each element is. Thus: the numbers 1 through 12 that are even and divisible by 3 are 6 and 12, so, the numbers that are even or divisible by 3 are 2, 3, 4,