This preview has intentionally blurred sections. Sign up to view the full version.View Full Document
Unformatted text preview: Chapter 0. Preliminaries 1. Some Definitions • A Population is the entire collection of objects or outcomes about which information is sought. • A Sample is a subset of a population, containing the objects or outcomes that are actually observed. • A Simple Random Sample (SRS) of size n is a sample chosen by a method in which each collection of n population items is equally likely to comprise the sample. 2. Random Variables • Random Variable : X , Y , Z , . . . Discrete Continuous Cumulative Distribution Function Probability Function 3. Discrete Distribution • Binomial, Poisson, Geometric, . . . • X ∼ Bernoulli( p ) • Y ∼ Binomial( n, p ) 1 4. Continuous Distribution • Exponential, Laplace, Cauchy, Uniform, Normal, . . . f ( x ) = 1 b h parenleftbigg x − a b parenrightbigg , where h ( · ) is a standard form of distribution, a is a location parameter and b is a scale parameter....
View Full Document
This note was uploaded on 07/22/2011 for the course STA 4502 taught by Professor Staff during the Spring '08 term at University of Florida.
- Spring '08