01:960:211 Lecture Notes - Lecture 6: Random Variable, Standard Deviation

• School: Rutgers University
• Department: Statistics and Biostatistic
• Course: 01:960:211
• Professor: professor Agre

Document Summary

Random variable: variable that assumes numerical value associated with the random outcomes of an experiment. Discrete: random variables that can assume a countable number of valubles (can be 1 or 2,finite or infinite) Continuous: random variables that assume values corresponding to any of the points within one or more intervals (infinite and uncountable) Probability distribution of a discrete random variable: graph, table, formula specifying probability associated with each possible value the random variable can assume. 1) p(x) 0 for all values of x. Where the sum of p(x) is over all possible values of x. Distribution is to graph!, refers to picture. The mean or expected value of a discrete or random variable: Population variance ( 2) of a random variable: the average of the square difference x from the population mean u, The square distance is also a random value : (x- )2.