BUSS1020 Lecture Notes - Lecture 5: Weighted Arithmetic Mean, Random Variable, Collectively Exhaustive Events

• School: University of Sydney
• Department: Business Studies
• Course: BUSS1020
• Professor: All

Document Summary

Random variable (rv) represents possible outcomes from an uncertain event. Numerical rvs can be discrete/continuous: discrete random variable, set of all possible outcomes is finite/countably infinite, e. g. rolling a die twice, continuous random variable, values at every point over a given interval, e. g. temperature, financial returns. Probability distribution for a numerical discrete rv is mutually exclusive+ collectively exhaustive; but there is an associated probability of the occurrence of each (prob varies) Expected value (or mean) of discrete rv is the weighted average. Calculated by multiplying observations with respective probabilities and adding together: Variance of a discrete random variable, where standard dev is square root. 3 forms of discrete probability distributions; binomial, poisson, hypergeometric; in questions, make sure to use the appropriate distribution. Binomial distribution shape: when p is very low (event has low chance of success) left skewed shape, when p near 0. 5 more symmetrical shape, when p very high right skewed shape.