Post on 06-Jan-2018
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7: The Logic of Sampling
Introduction• Nobody can observe everything• Critical to decide what to observe• Sampling
– Process of selecting observations• Probability sampling vs.
nonprobability sampling
History of Sampling• Developed hand in hand with
political polling• 1936: Literary Digest poll
– 10 million ballots were sent to people in telephone directories and automobile owner lists
– 2 million responded: 57% for Alf Landon, 43% for FDR
– Actual results: 61% for FDR
Nonprobability Sampling• Used when probability samples
can’t be selected• Four types:
1. Reliance on available subjects2. Purposive or judgmental sampling3. Snowball sampling4. Quota sampling
Reliance on Available Subjects
• Extremely risky - be cautious in generalizing
• Used frequently• Justified if:
– Want to study people passing the sampling point at a specified time
– Less risky methods are not feasible
Purposive or Judgmental Sampling
• May be appropriate to select sample based on judgment and purpose of study
• Used for pretests• Used to study a small subset of a
larger population• Used to study deviant cases
Snowball Sampling• Accidental sampling• Common in qualitative field
research• Appropriate when members of
special populations are hard to locate
• Collect data on a few members and then ask if they know others
• Used primarily for exploratory purposes
Quota Sampling• Addresses the issue of
representativeness• Matrix- describe characteristics of
population• Collect data from people having
characteristics of a given cell• Several problems
– Quota frame must be accurate– Biases may exist
Selecting Informants• Respondents
– People who provide information about themselves
• Informants – Members of the group who can talk
directly about the group• Select informants who are typical
of the groups
The Logic of Probability Sampling
• If everyone was the same…• But humans are quite different• Sample must contain same
variations that exist in the population
• Isn’t that simple and there are ways researchers mess up
Conscious and Unconscious Sampling
Bias• What happens when you select
people who are convenient for study?
• Personal leanings may affect the sample– May consciously or unconsciously
avoid interviewing certain people• Bias
– Those selected are not “typical” or “representative” of the larger population
Representativeness and Probability of Selection
• Sample is representative if…• Samples don’t have to be
representative in all respects: just to those characteristics relevant to the study
• EPSEM• Seldom perfectly represent the
population• Two advantages of probability
sampling1. More representative2. Permits us to estimate the accuracy of the
sample
Probability Sampling Theory
• The ultimate purpose of sampling• Probability sampling enhances
likelihood• Random selection
Sampling Distribution
Sampling Distribution• Sample size = 1
Sampling Distribution• Sample size = 2
Sampling Distribution• Sample size = 3 & 4
Sampling Distribution• Sample size = 5 & 6
Sampling Distribution
Sampling Distribution
Sampling Distribution• s= P x Q n• Contains 3 factors:
1. The population parameters (P & Q)2. The sample size (n)3. The standard error (s)
Sampling Distribution
Populations and Sampling Frames
• Less than perfect conditions exist in the field for sampling
• Sampling frame• Where can you get a list?• Omissions are inevitable
Types of Sampling Designs• Seldom choose simple random
sampling• Two reasons
1. Not feasible2. May not be most accurate method
Simple Random Sampling• Basic sampling method• Single number is assigned • Table of random numbers or
computer program
Systematic Sampling• Every kth element is chosen• First element selected at random
– Systematic sample with a random start
• Sampling interval• Sampling ratio• Virtually identical to SRS• Pay attention to the arrangement
of elements in the list
Stratified Sampling• Modification of two previous methods• Obtain a greater degree of
representativeness• Homogeneous subsets• Select number from each• Two methods of stratification
1. Sort into groups, select based on proportion of population
2. Put groups in continuous list, select systematic sample
Multistage Cluster Sampling
• Lists may not be available• Listing and sampling• Makes impossible studies possible• Highly efficient but less accurate
sample– Two sampling errors
• Stratification can be used• Probability proportionate to size
(PPS)• Disproportionate sampling and
weighting
Probability Sampling in Review
• Most effective method for the selection of study elements
• Avoids biases• Permits estimates of sampling
error