Textbook Notes (362,796)
Psychology (9,545)
PSYB01H3 (585)
Chapter 5

# Chapter 5 Notes 97-03.doc

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School
University of Toronto Scarborough
Department
Psychology
Course
PSYB01H3
Professor
David Nussbaum
Semester
Summer

Description
PSYB01 Chapter 5 – Sampling and Survey Research Selecting Research Participants - Sampling: the selection of individuals or other entities to represent a larger population - Census: to study the entire population of interest - Better to survey a limited number so there are more resources for follow-up procedures Sample Planning - Define the Population o Students, disabled persons, elderly and adult samples report similar levels of happiness o When Dieners analyzed surveys of happiness in countries around the world, the average level of happiness varied markedly (satisfaction with life domains varies across cultures) o Cross-population generalizability: compare results obtained from samples of different populations - Define Sample Components o Elements: elementary units, individual member of population whose characteristics are to be measured o Sampling frame: List of all elements in a population o Population: Entire set of individuals or other entities to study o Representative sample: “looks like” population from which it was selected (in unrepresentative sample, some characteristics are overrepresented or underrepresented) o Sample generalizability depends on the amount of sampling error (difference between sample and population) o Estimating Sampling Error  Inferential Statistics: tool for calculating sampling error  Sampling distributions for many statistics have a normal shape  Random Sampling Error: Variation owing purely to chance  Sample Statistic: value of a statistic such as a mean, computed from sample data PSYB01 Chapter 5 – Sampling and Survey Research  Population Parameter: Value of a statistic computed using the data for an entire population. Sample statistic is an estimate of a population parameter Sampling Methods - Probability Sampling Methods: Probability of selection is known and is not zero - Non-probability Sampling Methods: Sampling methods that do not let us know in advance the likelihood of selecting each element - Probability of Selection: likelihood that an element will be selected from the population for inclusion in the sample Probability Sampling Methods - These methods have no systematic bias (nothing but chance determines which elements are included in the sample) - Four most common methods for drawing random samples o Simple Random Sampling: procedure where cases are identified on basis of chance  Random digit dialing: machine dials random numbers within the phone prefixes o Systematic Random Sampling: variant of simple random sampling  First element is selected randomly and then every nth element is selected  Watch out for periodicity (sequence varies in some regular, periodic pattern) (e.g. houses counted and the house on northwest side always chosen because of sampling interval [number of cases from one sampled case to another])  In that situation, starting point needs to be changed o Stratified Random Sampling: uses information known about population prior to sampling to make sampling process more efficient  Ensures appropriate representation of elements across strata  Proportionate Stratified Sampling: ensures that sample is selected so that the distribution of characteristics in the sample matches the population  Disproportionate Stratified Sampling: Sampling where characteristics of sample are disproportionate to population PSYB01 Chapter 5 – Sampling and Survey Research o Cluster Sampling: Sampling selected in two or more stages, first random selection then random selection of elements within clusters  Clusters are naturally occurring, mixed aggregate of elements of a population Nonprobability Sampling Methods - Availability Sampling (Convenience sampling): available or easy to find, haphazard, accidental - Quota Sampling o Intended to overcome the flaw of availability sampling: that sample will just consist of whoever or whatever is available o Must match percentage of desired population study o No matter what type of sample you draw, your sample will be less representative if more potential respondents refuse to participate Writing Survey Questions - Avoid confusing phrasing o Simple direct approach to asking a question minimizes confusion (shorter words and sentences and keep total number of words to 20 or fewer) o Avoid “don’t” or “not” in questions, double negatives are confusing o Avoid double-barrelled questions: asking two questions but allow only one answer o Use filter questions: survey question used to identify a subset of respondents and then asked other questions  Avoids skip patterns (Combination of
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