EC255 Lecture Notes - Lecture 4: Mutual Exclusivity, Statistical Parameter, Xu
Document Summary
Probability is the basis for inferential statistics (sampling a population) When the population parameter is unknown = extract sample = sample statistic computed = estimate parameter with statistic = repeat all. 3 techniques for counting the possibilities in an experiment are the mn counting rule, the. 4 types of probability are marginal probability, conditional probability, joint probability, and union probability. Classical method of assigning probabilities: probabilities are assigned based on laws and rules. The probability of an individual event occurring is determined as the ratio of the number of items in a population containing the event (ne) to the total # of items in the population (n) * ne can never be greater than n, the highest value of any probability is 1. * probabilities are nonnegative proper fractions or nonnegative decimal values less than or equal to 1. A priori: probabilities can be determined prior to the experiment.
