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Chapter 7
Sampling, Significance Levels, and Hypothesis Testing
Three scientific traditions critical to experimental research
Sampling
Significance levels
Hypothesis testing
Copyright c 2001 The McGrawHill Companies, Inc. 1
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 McGrawHill Companies, Inc. 2
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 McGrawHill Companies, Inc. 3
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 McGrawHill Companies, Inc. 4
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 McGrawHill Companies, Inc. 5
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