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# SOAN 2120 Study Guide - Final Guide: Simple Random Sample, Central Limit Theorem, Sampling Frame

Department
Sociology and Anthropology
Course Code
SOAN 2120
Professor
David Walters
Study Guide
Final

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Sampling
- qualitative research uses nonrandom samples or nonprobability samples
o this means they rarely determine the sample size in advance and have
limited knowledge about the larger group from which the sample is
taken
Types of Nonprobability Sampling
- Haphazard
o Get any cases in the manner that is convenient
o Cons: can produce ineffective, unrepresentative samples
o Eg: television interviewers on the street they conveniently go to
whoever is around and interview them
- Quota Sampling
o Get a preset number of cases in each of several predetermined
categories that will reflect the diversity of the population
o Researcher identifies relevant categories of people (i.e. males or
females), then decides how many to get in each category
o Improvement over haphazard because it ensures some differences
- Purposive
o Get all possible cases that fit particular criteria using various methods
o Expert uses judgment in selecting cases with a specific purpose in
mind
o Appropriate in three situations
Select unique cases that are informative
Select members of a difficult to reach population
When research wants to identify certain types of cases for in-
depth investigation
- Snowball
o Get cases using referrals from one or a few cases, and then referrals
from those cases, and so forth.
o Method for identifying and sampling the cases in a network
o It essentially “snowballs”
- Deviant Case
o Get cases that substantially differ from the dominant pattern (special
type of purposive)
- Sequential
o Get cases until there is no additional information or new
characteristics
o A researcher gathers cases until the amount of new information or
diversity of cases is filled

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Types of Probability Sampling
- Simple Random
o Researcher develops an accurate sampling frame, selects elements
from the sampling frame according to the mathematically random
procedure, then locates the exact element that was selected for the
inclusion in the sample
o Researcher uses a list of random numbers to decide which elements
to select
o Example on page 117 (red and white marbles)
o Sampling distribution = the set of many random samples
o Central limit theorem = tells us that as the number of different
random samples in a sampling distribution increases toward infinity,
the pattern of samples and the population parameter become more
predictable
- Systematic Sampling
o Simple random sampling but with a shortcut for random selection
o First step is to number each element in the sampling frame
o Researcher calculates a sampling interval, and the interval becomes
his or her quasi-random selection method
- Stratified Sampling
o Researcher first divides the population into sub-populations (strata)
on the basis of supplementary information
o Then the researcher draws a random sample from each subpopulation
o In this type of sampling, the researcher controls the relative size of
each stratum
o It produces samples that are more representative of the population
than simple random sampling if the stratum information is accurate
- Cluster Sampling
Researchers lack a good sampling frame for a dispersed
population
The cost to reach a sampled element is very high
o A cluster is a unit that contains final sampling elements itself
o Researcher first samples clusters then draws a second sample from
within the clusters selected in the first stage of sampling
o Advantage? Create a good sampling frame
o Researcher draws several samples in stages
Stage 1 is random sampling of big clusters
Stage 2 is random sampling of small clusters within the big
bluster
Stage 3 is sampling of elements from the small clusters
o Less expensive but also less accurate

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Survey Research
Steps in the Process of Survey Research
Step 1:
- develop hypotheses
- decide on type of survey
- write survey questions
- design layout
Step 2:
- plan how to record data
Step 3:
- decide on target population
- get sampling frame
- decide on sample size
- select sample
Step 4:
- locate respondents
- conduct interviews
- record data
Step 5:
- enter data into computers
- recheck all data
- perform statistical analysis on data
Step 6:
- describe methods and findings in report
- present findings
Twelve Things to Avoid When Writing Survey Questions!
1. jargon, slang, and abbreviations
2. ambiguity, confusion, and vagueness
3. emotional language
4. prestige bias
5. double-barreled questions
6. do not confuse beliefs with reality
8. asking questions that are beyond respondents’ capabilities
9. false premises