Statistical Sciences 2244A/B Chapter Notes - Chapter 5: Central Limit Theorem, Quantile, Normal Distribution

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A random variable is a variable having a single numerical value, determined by chance, A probability distribution for a discrete random variable describes the probability for each for each outcome of some procedure value of the random variable. A discrete random variable has either a finite number of values or a countable number of values. That is, the number of possible values that x can assume is 0, or 1, or 2, etc. A continuous random variable has infinitely many values and those values are often associated with measurements on a continuous scale with no gaps or interruptions. In this chapter, continuous probability distributions are presented. If a continuous random variable has a distribution with a graph that is symmetric and bell-shaped, and can be described by the equation given, we say it has a normal distribution. The normal distribution is determined by two parameters: the mean, , and standard deviation, .

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