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Chapter Summaries - Test 2

7 Pages
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Department
Sociology
Course Code
SOC200H1
Professor
Eric Fong

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Chapter 7 – Logic of Sampling
Nonprobability Sampling
Social research is often conducted in situations that do not permit the kinds of probability samples used in
large-scale social surveys (i.e. homelessness)
Although appropriate to some research purposes (qualitative research), nonprobability sampling methods
cannot guarantee that the sample being observed is representative of the whole population
There are four types of nonprobability sampling:
-Reliance on Available Subjects: i.e. stopping people at a street corner or some other location
-Purposive or Judgemental Sampling: sometimes its appropriate to select a sample on the basis of
knowledge of a population, its elements, and the purpose of the study
-Snowball Sampling: whereby each person interviewed may be asked to suggest additional people
for interviewing
-Quota Sampling: 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
Probability Sampling
EPSEM (equal probability of selection method)a sample design in which each member of a population
has the same chance of being selected into the sample
Probability sampling does offer two advantages:
-Typically more representative than other types of sample because biases are avoided
-Probability theory permits us to estimate the accuracy or representativeness of the sample
Elementthat unit of which a population is composed and which is selected in a sample
Parameterthe summary description of a given variable in a population
Statisticthe summary description of a variable in a sample, used to estimate a population parameter
Sampling errorthe degree of error to be expected in probability sampling
Confidence levelthe estimated probability that a population parameter lies within a given confidence
interval (i.e. we are 95% confident that between 35%-45% of all kids like smarties)
Confidence intervalthe range of values within which a population parameter is estimated to lie
There are four types of probability sampling:
-Systematic sampling: involves the selection of every kth member from a sampling frame; this
method is more practical than simple random sampling and is almost functionally equivalent
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-Stratification: the process of grouping the members of a population into relatively homogeneous
strata before sampling, improves the representativeness of a sample by reducing the degree of
sampling error
-Multistage Cluster Sampling: complex but is frequently used when a list of all the members of a
population does not exist. Typically, researchers must balance the number of clusters and the size
of each cluster to achieve a given sample size. Stratification can be used to reduce the sampling
error involved in multistage cluster sampling
oProbability proportionate to size (PPS) is a special efficient method for multistage cluster
sampling
oIf the members of a population have unequal probabilities of selection into the sample,
researchers must assign weights to the different observations made, in order to provide a
representative picture of the total population. The weight assigned to a particular sample
member should be the inverse of its probability of selection
Ethics of Sampling
Probability sampling always carries a risk of error; researchers must inform readers of any errors that
might make results misleading
When nonprobability sampling methods are used to obtain the breadth of variations in a population,
researchers must take care not to mislead readers into confusing variations with whats typical in the
population
Chapter 8 – Experiments
The Classical Experiment
-Tests the effect of an experimental stimulus (independent variable) on a dependent variable
through the pretesting and posttesting of experimental and control groups
oPretesting: the measurement of a dependent variable among subjects before they are
exposed to a stimulus represent an independent variable
oPosttesting: the remeasurement of a dependent variable among subjects after theyve been
exposed to a stimulus representing an independent variable
- It is generally less important that a group of experimental subjects be representative of some
larger population than that experimental and control groups be similar to each other
oExperimental group: a group of subjects to whom an experimental stimulus is
administered
oControl group: a group of subjects to whom no experimental stimulus is administered
and who resemble the experimental group in all other respects
-A double-blind experiment guards against experimenter bias because neither the experimenter nor
the subject knows which subjects are in control and experimental groups
Selecting Subjects
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Description
Chapter 7 Logic of Sampling Nonprobability Sampling Social research is often conducted in situations that do not permit the kinds of probability samples used in large-scale social surveys (i.e. homelessness) Although appropriate to some research purposes (qualitative research), nonprobability sampling methods cannot guarantee that the sample being observed is representative of the whole population There are four types of nonprobability sampling: - Reliance on Available Subjects: i.e. stopping people at a street corner or some other location - Purposive or Judgemental Sampling: sometimes its appropriate to select a sample on the basis of knowledge of a population, its elements, and the purpose of the study - Snowball Sampling: whereby each person interviewed may be asked to suggest additional people for interviewing - Quota Sampling: 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 Probability Sampling EPSEM (equal probability of selection method) a sample design in which each member of a population has the same chance of being selected into the sample Probability sampling does offer two advantages: - Typically more representative than other types of sample because biases are avoided - Probability theory permits us to estimate the accuracy or representativeness of the sample Element that unit of which a population is composed and which is selected in a sample Parameter the summary description of a given variable in a population Statistic the summary description of a variable in a sample, used to estimate a population parameter Sampling error the degree of error to be expected in probability sampling Confidence level the estimated probability that a population parameter lies within a given confidence interval (i.e. we are 95% confident that between 35%-45% of all kids like smarties) Confidence interval the range of values within which a population parameter is estimated to lie There are four types of probability sampling: - Systematic sampling: involves the selection of every kth member from a sampling frame; this method is more practical than simple random sampling and is almost functionally equivalent www.notesolution.com
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