AP statistics chapter 16 by Stats modelling the world third edition by David E. Bock
● Vocab- Random variable - A random variable assumes any of several different numeric values as a result of some random event. Random variables are denoted by a capital letter such as X. ● Discrete random variable - A random variable that can take one of an infinite number of distinct outcomes is called a discrete random variable. ● Continuous random variable - A random variable that can take any numeric value within a range of values is called a continuous random variable. The range may be infinite or bounded at either or both ends. ● Probability model - The probability model is a function that associates a probability P with each value of a discrete random variable X, denoted or with any interval of values of a continuous random variable. ● Expected value - The expected value of a random variable is its theoretical long-run average value, the center of its model. It is found by summing the products of variable values and probabilities. ● Picture - We can use the probability model for a discrete random variable to find its expected value and its standard deviation.
● Vocab- Random variable - A random variable assumes any of several different numeric values as a result of some random event. Random variables are denoted by a capital letter such as X. ● Discrete random variable - A random variable that can take one of an infinite number of distinct outcomes is called a discrete random variable. ● Continuous random variable - A random variable that can take any numeric value within a range of values is called a continuous random variable. The range may be infinite or bounded at either or both ends. ● Probability model - The probability model is a function that associates a probability P with each value of a discrete random variable X, denoted or with any interval of values of a continuous random variable. ● Expected value - The expected value of a random variable is its theoretical long-run average value, the center of its model. It is found by summing the products of variable values and probabilities. ● Picture - We can use the probability model for a discrete random variable to find its expected value and its standard deviation.