STAT 110 Lecture Notes - Lecture 2: Statistical Inference, Stratified Sampling, Simple Random Sample
8 Sep 2016
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The goal of statistical inference is to use the information in a sample of individuals to describe a larger population of individuals. Sampling design- the way we select a sample from a population. A convenience sample- collects individuals that are the easiest to contact. Voluntary response sample- includes individuals who choose themselves to be included. To avoid systematic underrepresentation, or bias, use impersonal chance to select individuals. Simple random sampling (srs)- the sample size or n has the same chance of being selected as any other sample of size. Each individual has the same chance of being selected. Table of random digits- a list of numbers determined at random. Sampling frame- a list of all individuals in the population, (anyone who qualifies to be in a sample) When selecting a sample of individuals, our goal is to choose one that is representative of the population. Stratified sampling- individuals are first separated into strata (different groups; gender, race, income class, etc. )
