BNAD 276 Lecture Notes - Lecture 6: Probability Distribution, Cumulative Distribution Function, Random Variable

• School: University of Arizona
• Department: Business Administration
• Course: BNAD 276
• Professor: brentmarinan

Document Summary

Has boundaries, a on left and b on right. Continuous random variables and the uniform probability distribution- We cannot assign a nonzero probability to each infinitely uncountable value and still have the probabilities sum to one. Since p(x=a) and p(x=b) both equal zero. The following holds true for continuous random variables. If you want to find the area between two outcomes on a bell curve (a and b), you would take p(x 0 for all possible values of x. The area under f(x) over all values of x equals one. F(x) of a continuous random variable x : For any value x of the random variable x, the cumulative distribution function f(x) is computed as. As a result, p(a < x < b) = f(b) f(a) The one that looks like a rectangle.