STAB22H3 Lecture Notes - Lecture 8: Exponential Distribution, Probability Distribution, Central Limit Theorem
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Example: the random number generator will spread its output uniformly across the entire interval from 0 to 1 as we allow it to generate a long sequence of numbers. The results of many trials are represented by the density curve of a uniform distribution. A continuous random variable x takes all values in an interval of numbers. The probability distribution of x is described by a density curve. The probability of any event is the area under the density curve and above the values of x that make up the event. Let"s look at the examples from the previous lecture: Example: binomial distribution, n = 500, p = 0. 4. Example: a sample survey asks a nationwide random sample of 2500 adults if they agree or disagree that i like buying new clothes, but shopping is often frustrating and time-consuming . Suppose that 60% of all adults would agree if asked this question.
