STAT 202 Lecture Notes - Lecture 1: Random Variable, Square Root, Probability Distribution

• School: Drexel University
• Department: Business Statistics
• Course: STAT 202
• Professor: Christopher T Gaffney

Document Summary

A random variable x can take values 2. If x is discrete, then there are accountable number of values x that can be taken if x is continuous, then there are an uncountable number of values that can be taken. For any two values x1 and x2 there is always another value x3 in between. Let x be a discrete random variable (rv) with n possible values. Then the expected value (mean) of x is e(x)=u=n, i=i,xi,p(xi) The variance of x is sigma^2 = sum,n,i=i(xi-u)^2p(xi) The standard deviation = sigma = square root sigma^2. Ex) flip 3 coins {hhh, htt, tht, tth, hht, hth, thh, ttt} each has a probability of 1/8, let x be the number of heads p(x=0) = 1/8 p(x=1) = 3/8 p(x=2) = 3/8 p(x=3) = 1/8. The pdf (probability distribution function) gives the probability that x takes on a particular value = p(x=x)