MAT 121 Lecture Notes - Lecture 8: Random Variable, Square Root, Binomial Distribution
20 Oct 2014
School
Department
Course
Professor
Document Summary
Mat 121: elementary statistics and probability- lecture 9: random variables and. Random variables: random variables= value is a numerical outcome, discrete random= has countable number. = denoted by x": continuous random= all values in an interval of numbers (measurements) = example: number of children in a family, number of students in a class. = example: height, weight: probability distribution= description that gives the probability for each value of the random variable. = expressed as a graph, table, or formula. Probability distribution: requirements, probability must be a decimal, the sum of probabilities must equal 1. *note that this formula does not define the probability because probability is always a. No- the sum of the probabilities does not equal 1, it is . 9. No- the sum equals 1, but one of the values is negative. Probability histogram: probability histogram= similar to relative frequency histogram. = bars are centered at random variables and their heights correspond to the probabilities.
