STAB22H3 Lecture Notes - Lecture 8: Bayesian Probability, Iten, American Express

• School: UTSC
• Department: Statistics
• Course: STAB22H3
• Professor: Mahinda Samarakoon

Document Summary

I the sample space of a random phenomenon is the set of all possible outcomes. Sample space: s = {1, 2, 3, 4, 5, 6} I an event is an outcome or a set of outcomes of a random phenomenon. That is, an event is a subset of the sample space. I each occasion upon which we observe a random phenomenon is called a trial. I example: the sample space (s) for two tosses of a coin to is s. S = {hh, ht , th, tt } Then obtaining exactly one head is an event, call it a, then. I when thinking about what happens with combinations of outcomes, things are simpli ed if the individual trials are independent. I roughly speaking, two trials are independent when the outcome of one trial does not in uence or change the outcome of another. I example: coin ips are independent (independent/not indep). Let m represent the number of heads obtained.