STAT 200 Lecture Notes - Probability Density Function, Probability Distribution, Cumulative Distribution Function
Document Summary
Random variable- numerical characteristic of each even in a sample space, or equivalently, each individual population. Discrete random variable- has a countable set of distinct possible values. Continuous random variable- such a way to value (to any number of decimal places) within some interval is a possible value. Probability distribution (also called the probability distribution function)- any table, graph, or formula that gives each possible value and the probability of that value. The total of all probabilities across the distribution must be 1, and each individual probability must be between 0 and 1, inclusive. Cumulative probability- because to find the answer, we simply add probabilities for all values qualifying as less than or equal to the specified value. Cumulative distribution- a listing of all possible values along with the cumulative probability for each value. Expected value- synonym for mean value in the long run.
