# Sampling Procedures

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```					Course Content
I.     Introduction to the Research Process
II.    Identification of the Research Problem
III.   Development of the Research Question or
Hypothesis
IV.    Formulation of the Research Methods
V.     Analysis and Interpretation of the Collected
Data
VI.    Writing the Research Report
The Scientific Method
1.   Develop the problem
2.   Develop a theoretical solution to the problem
3.   Formulate the hypothesis or question
4.   Formulate the research plan (methods)
5.   Collect and analyze the data
6.   Interpret the results and form conclusions
7.   Refine the theory
Formulation of the
Research Methods
A.   Selecting the Appropriate Design
B.   Selecting the Subjects
C.   Selecting Measurement Methods &
Techniques
D.   Selecting Instrumentation
Formulation of the
Research Methods
E.   Developing Procedures & Protocol
F.   Using a Pilot Study
G.   Selecting the Appropriate Analysis
Techniques
H.   Developing a Timeline & Budget
I.   Collecting the Data
Sampling
Procedures
Definitions
 Population – group of things (people)
having one or more common
characteristics
 Sample – representative subgroup of the
larger population
 Used  to estimate something about a
population (generalize)
 Must be similar to population on characteristic
being investigated
Representative
Sampling Methods
Probability Sampling      Non-Probability Sampling
   Simple random sampling     Deliberate (quota)
   Stratified random           sampling
sampling                   Convenience sampling
   Systematic sampling        Purposive sampling
   Cluster (area) sampling
   Multistage sampling
Simple Random Sampling
   Equal probability
   Techniques
 Fishbowl  (with replacement & w/o replacement)
 Table of random numbers

 Most   representative group
 Difficult   to identify every member of a population
Stratified Random Sampling
   Technique
 Divide population into various strata
 Randomly sample within each strata
 Sample from each strata should be proportional
 Better in achieving representativeness on control
variable
 Difficult to pick appropriate strata
 Difficult to ID every member in population
Systematic Sampling
   Technique
   Use “system” to select sample (e.g., every 5th item in
alphabetized list, every 10th name in phone book)
   Quick, efficient, saves time and energy
   Not entirely bias free; each item does not have equal chance to
be selected
   System for selecting subjects may introduce systematic error
   Cannot generalize beyond pop actually sampled
Cluster (Area) Sampling
   Randomly select groups (cluster) – all members
of groups are subjects
   Appropriate when
 youcan’t obtain a list of the members of the
population
 have little knowledge of pop characteristics
 Pop is scattered over large geographic area
Cluster (Area) Sampling
 More   practical, less costly
 Conclusions should be stated in terms of
cluster (sample unit – school)
 Sample size is # of clusters
Multistage Sampling
   Stage 1
 randomly   sample clusters (schools)
   Stage 2
 randomly   sample individuals from the schools
selected
Sampling Methods
Probability Sampling      Non-Probability Sampling
   Simple random sampling     Deliberate (quota)
   Stratified random           sampling
sampling                   Convenience sampling
   Systematic sampling        Purposive sampling
   Cluster (area) sampling
   Multistage sampling
Deliberate (Quota) Sampling
   Similar to stratified random sampling
   Technique
 Quotas  set using some characteristic of the
population thought to be relevant
 Subjects selected non-randomly to meet quotas (usu.
convenience sampling)
 selection bias
 Cannot set quotas   for all characteristics important to
study
Convenience Sampling
   “Take them where you find them” - nonrandom
   Intact classes, volunteers, survey respondents
(low return), a typical group, a typical person
   Use post hoc analysis to show groups were
equal at the start
Sample Size
   Critical factor is whether sample is representative
   Necessary sample size depends on population size
   Recommendations:
   Use tables from books
   30 per group
   Descriptive studies – 10-20% of population
   No more than 50% of population
   Statistical power
   Attrition
Other Sampling Considerations
   Random assignment
   Sampling of treatments (experimental research)
   Use post hoc analysis to show groups were equal at
the start
   Since random sampling is often impossible, sample
must be selected on some theoretical basis
   Be careful with generalizations
When Selecting Subjects …
   Are subjects with special characteristics
necessary for your research? (age, gender,
trained/untrained, expert/novice, size, etc.)
   Can you obtain the necessary permission and
cooperation from the subjects?
   Can you find enough subjects?

   Interaction among selection of subjects,
treatments, and measures is essential for
experimental studies.
Reporting Subjects
   State how many subjects were selected
   Describe how the subjects were selected
   Discuss whether any subjects were lost during
the study and why
   Explain why the subjects were selected
   Describe subject characteristics that are
pertinent to study – be very specific
   Identify procedures taken to protect the subjects

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