Chapter 7: The Logic of Sampling Flashcards
Any technique in which samples are selected in some way not suggested by probability theory.
Nonprobability Sampling
What are the four types of nonprobability sampling?
(1) Reliance on available subjects, (2) purposive of judgemental sampling, (3) snowball sample, and (4) quota sampling
Stopping people on the street is an example of
Reliance on available subjects (aka haphazard or convenience sampling
A type of nonprobability sampling in which the units to be observed are selected on the basis of the researcher’s judgment about which ones will be the most useful or representative.
Purposive Sampling or Judgemental Sampling
A nonprobability-sampling method, often employed in field research, whereby each person interviewed may be asked to suggest additional people for interviewing
Snowball Sampling (aka Chain Referral)
A type of nonprobability sampling in which units are selected into a sample on the basis of prespecified characteristics, so that the total sample will have the same distribution of characteristics assumed to exist in the population being studied
Quota Sampling
Someone who is well versed in the social phenomenon that you wish to study and who is willing to tell you what he or she knows about it.
Informant
People who provide information about themselves to social researchers
Respondents
The general term for samples selected in accordance with probability theory, typically involving some random-selection mechanism.
Probability Sampling
What are some specific types of probability sampling?
EPSEM, PPS, Simple Random Sampling, and Systematic Sampling
What is the advantage of probability sampling?
It guarentees the sample we observed is representative of the whole population being studied
What is the fundamental idea behind probability sampling?
In order to provide useful descriptions of the total population, a sample of individuals from a population must contain essentially the same variations that exist in the population.
Those selected are not typical pr representative of the larger population they’ve been chosen from
Sampling Bias
That quality of a sample having the same distribution of characrestics as the population from which it was selected. By implication, descriptions and explanations derived from an analysis of the sample may be assumed to represent similar ones in the population.
Representativeness
A sample design in which each member of a population has the same chance of being selected into the sample
EPSEM (Equal Probability of Selection Method)
What are two major advantages of probability sampling?
Lack of bias and accuracy
The units of which a population is composed and which is selected in a sample. Distiguished from units of analysis which are used in data analysis
Element
The theoretically specified aggregation of the elements in a study
Population
The aggregation of elements from which a sample is actually selected
Study Population
A sampling method in whuchg each element has an equal chance of selectuib independent of any other event in the selection process. (Ex. flipping a coin)
Random Selection
That elemenet or set of elements considered for selection in some stage of sampling
Sampling Unit
The summary description of a given variable in a population
Parameter
What are two reasons for using random selection?
(1) Serves as a check on conscious or subconscious bias & (2) offers access to the body of probability theory
A branch of mathematics that provides the tolls researchers need (1) to devise sampling techniques that produce representative samples and (2) to statistically analyze the results of their sampling.
Probability Theory
The summary description of a variable in a sample, used to estimate a population parameter.
Statistic
The degree of error to be expected in probability sampling. Formula contains three factors: The parameter, the sample size, and the standard error
Sampling error
Sampling Error Formula
s= √ (PxQ/n)
Population parameters for the binomial in sampling error formula
P & Q
What percent of samples must fall within plus or minus two standard errors of the true value in probability theory?
95%
What percent of samples must fall within plus or minus three standard errors of the true value in probability theory?
99.9%
The estimated probability that a population parameter lies within a given confidence interval.
Confidenece Level
The range of values within which a population parameter is estimated to lie.
Confidence Interval
That list or quasi list of units composing a population from which a sample is selected.
Sampling Frame
Findings based on a sample can be taken as representing only…
the aggregation of elements that compose the sampling frame
Researchers must research and correct if possible
omissions to the sampling frame
To be geneeralized even to the population composing the sampling frame…
all elements myst have eqeual representation in the frame
A type of probability sampling in which the units composing a population are assigned numbers. A set of random numbers is then generated, and the units having those numbers are included in the sample.
Simple Random Sampling
A type of probability sampling in which every kth unit in a list is selected in the sample–for example, every 25th student in the college directory
Systematic Sampling
The dtandard distance (k) between elements selected from a population for a sample ( = Population size/Sample size)
Sampling Interval
The proportion of elements in the population that are selected to be in a sample ( = Sample size/Population size)
Sampling Ratio
The grouping of the units composing a population into homogeneous groups (or strata) before sampling. This procedure, which may be used in conjunction with the simple random, systematic, or cluster sampling, improves the representativeness of a sample.
Stratification
A multistage sampling in which natural groups (clusters) are sampled inititially, with the members of each selected group being subsampled afterward. For example, you might select aq sample of U.S. colleges and universities from a directory, get lists of the students at all the selected schools, then draw samples of students from each.
Cluster Sampling
Sampling error is reduced by what two factors?
(1) An incease in the sample size and (2) increased homogeneity of the elements being sampled.
This refers to a type of multistage cluster sample in which clusters are selected, not with equal probabilities (see EPSEM) but with probabilities proportionate to their sizes–as measured by the number of units tonbe subsampled
PPS (Probability Proportionate to Size)
Assigning different weights to cases that were selected into a sample with different probabilities of selection. In the simplest scenario, each case is given weight equal to the inverse of its probability of selection. When all cases have the same chance of selection, this is not necessary.
Weighting
