STT 201 Study Guide - Midterm Guide: Central Limit Theorem, Binomial Distribution, Conditional Probability
22 Feb 2013
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Sample space (s) = {all possible outcomes} Events (e) = {outcomes you want: null: nothing happens and p=0, sure: everything happens and p=1. Probability (p): (p) = where n=number of repetitions. Use ncr for at most: multiple trials: S = successes (p(f))f(p(s))s: complementation rule: finds the probability of at least one desired event happening. Conditional probability: probability of events are dependent on each other: p(a|b) , multiplication rule: P(a and b) = p(a)*p(b|a: addition rule: P(a or b) = p(a) + p(b) p(a and b) Unconditional probability: weighted average of conditional probabilities: p = , independence: Binomial distributions: distribution of number x of successes in n independent trials of an experiment with a constant probability p of success (aka a bell curve) Notation: mean = , standard deviation = . Types of distributions on bell curve: standard normal distribution: changes scale to be standard . = 1: general normal distributions: uses any scale ( general )
