tailieunhanh - Lecture Communication research: Asking questions, finding answers (2/e): Chapter 7 - Joann Keyton

Chapter 7 - Sampling, significance levels, and hypothesis testing. After reading this chapter, you should be able to: Identify the population and sampling frame to select an appropriate sample, argue for how results from a sample are generalizable to its population, use probability sampling procedures to produce a random sample, use nonprobability procedures to produce an appropriate sample,. | Chapter 7 Sampling, Significance Levels, and Hypothesis Testing Three scientific traditions critical to experimental research Sampling Significance levels Hypothesis testing 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 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 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 . | Chapter 7 Sampling, Significance Levels, and Hypothesis Testing Three scientific traditions critical to experimental research Sampling Significance levels Hypothesis testing 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 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 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 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 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 Nonprobability Sampling Does not rely on random selection Weakens sample-to-population representativeness Used when other techniques will not result in an adequate or appropriate sample Used when researchers desire participants with special experiences or abilities Nonprobability Sampling Techniques Convenience sample .