6. (Statistics, Economics, and Data Science through Probability Density Functions) Let a and y be two continuous random variables (i.e. characteristics distributed throughout a population). The joint density function of a and y is a function p of two variables such that the probability that (x, y) lies in a region D is P((r, y) in D) = | P(x, y) dA. Because probabilities aren't negative and are measured on a scale from 0 to 1, we know that a joint density function must satisfy the following condition: L. p(r, y) dr dy = 1. Suppose the joint density function for a pair of random variables X and Y is: Cx(1+y) if 0 < x< 1, 0
6. (Statistics, Economics, and Data Science through Probability Density Functions) Let a and y be two continuous random variables (i.e. characteristics distributed throughout a population). The joint density function of a and y is a function p of two variables such that the probability that (x, y) lies in a region D is P((r, y) in D) = | P(x, y) dA. Because probabilities aren't negative and are measured on a scale from 0 to 1, we know that a joint density function must satisfy the following condition: L. p(r, y) dr dy = 1. Suppose the joint density function for a pair of random variables X and Y is: Cx(1+y) if 0 < x< 1, 0
Calculus: Early Transcendentals
8th Edition
ISBN:9781285741550
Author:James Stewart
Publisher:James Stewart
Chapter1: Functions And Models
Section: Chapter Questions
Problem 1RCC: (a) What is a function? What are its domain and range? (b) What is the graph of a function? (c) How...
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