After reading this chapter, you should be able to: Describe the distinctions among population, sampling frame, and sample; identify the population and sampling frame to select an appropriate sample; argue for how results from a sample are generalizable to its population. | Chapter 7 Sampling, Significance Levels, and Hypothesis Testing Three scientific traditions critical to experimental research Sampling Significance levels Hypothesis testing Copyright c 2001 The McGraw-Hill Companies, Inc. Population and Sample Population – all units (people or things) possessing the attributes and characteristics of interest Sample -- subset of a population Sampling frame -- subset of units that have a chance to become part of the sample Researchers study the sample to make generalizations back to the population Copyright c 2001 The McGraw-Hill Companies, Inc. Defining the Population Choose the dimensions or characteristics meaningful to the hypothesis or research question Must be at least one common characteristic among all members of a population Must develop procedure to ensure representative sampling Copyright c 2001 The McGraw-Hill Companies, Inc. Addressing Generalizability Extent to which conclusions developed from data collected from sample can be | Chapter 7 Sampling, Significance Levels, and Hypothesis Testing Three scientific traditions critical to experimental research Sampling Significance levels Hypothesis testing Copyright c 2001 The McGraw-Hill Companies, Inc. Population and Sample Population – all units (people or things) possessing the attributes and characteristics of interest Sample -- subset of a population Sampling frame -- subset of units that have a chance to become part of the sample Researchers study the sample to make generalizations back to the population Copyright c 2001 The McGraw-Hill Companies, Inc. Defining the Population Choose the dimensions or characteristics meaningful to the hypothesis or research question Must be at least one common characteristic among all members of a population Must develop procedure to ensure representative sampling Copyright c 2001 The McGraw-Hill Companies, Inc. Addressing Generalizability Extent to which conclusions developed from data collected from sample can be extended to its population Sample is representative to the degree that all units had same chance for being selected Representative sampling eliminates selection bias Characteristics of population should appear to the same degree in sample Representativeness can only be assured through random sampling Copyright c 2001 The McGraw-Hill Companies, Inc. Probability Sampling The probability of any unit being included in the sample is known and equal When probability for selection is equal, selection is random Also known as random sampling Sampling error will always occur Copyright c 2001 The McGraw-Hill Companies, Inc. Types of Probability Sampling Simple random sampling Simplest and quickest Systematic sampling If used on a randomly ordered frame, results in truly random sample Stratified random sampling Random sampling within all subgroups Cluster sampling Random sampling within known clusters Copyright c 2001 The McGraw-Hill Companies, Inc. Nonprobability Sampling Does not .
