STAT 218 Chapter Notes - Chapter 4: Statistical Inference, Random Variable, Standard Deviation
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Next: learning how to apply the ideas to solving real work statistical problems and thus laying the foundation for inferential statistics. Random variable = a variable that gets a numerical value assigned based on the outcome of a chance event: examples: Discrete random variable = one which actually counts the possible responses. Continuous random variable = one that takes on the values in an interval. Binomial distribution = one in which the experiment consists of bernoulli trials and we are interested in counting the number of successes: one of the most widely encountered discrete distributions in the real world. Now lets generalize and simplify the process, there"s a pattern or a formula! If we use the same computer virus example and it asks what is the probability that less than 4 of these computers were infected? that"s just like saying less than or equal to.
