BUSS1020 Lecture Notes - Lecture 6: Probability Distribution, Random Variable, Poisson Distribution
19 Jul 2018
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Document Summary
In continuous distributions, we do not look at the probability of x, we look at the function of x. Definition of probability = number of occurrence / total number of observations. In a continuous distribution, the sum of all possibilities are infinite, therefore instead of p(x=xi) = 1, we use: Also means that the area under a curve = 1. Probabilities are always between 0 and 1, and are worked out by. A continuous random variable can assume any value on a continuum. P(a < x < b: thickness, height, weight, time required to complete a task, temperature, financial return. A cts rv can potentially take on any vale, depending on the ability to accurately and finely measure it. Some more cts rvs relevant to business: weight of cans, delivery times, download times, hotel occupancy rate, financial return. Instead of probabilities for each value of x, a continues rv has a probability density function.
