ECON 2B03 Lecture Notes - Lecture 11: Central Limit Theorem, Binomial Distribution, Random Variable

• School: McMaster University
• Department: Economics
• Course: ECON 2B03
• Professor: Hannah Holmes

Document Summary

Mean of a discrete random variable: the mean of a discrete fandom variable (i. e, the average or expected value") is denoted by e(x), px, or simply u(symbol). The expected value is the weighted average of all possible values of x, where the weights are the probabilities associated with the particular x values, i. e. E(x) = n sum symbol i -1 x1 x p(x = xi) Note that the variance denotes the average squared deviation from the mean, and is referred to as e[(x p)^2]. Using the rule of e(g(x)] = sum symbol(x)p(x x) and g(x) (x. P)^2, we obtain the formula for variance. Standard deviation: theta x is the square root of theta square x. The binomial" distribution is one of the most useful discrete distributions we shall use. A binomial probability distribution shows the probabilities associated with possible values of a discrete random variable that is generated by a type of experiment called a bernoulli process.