Study Guides (275,813)
CA (151,008)
UTM (6,138)
SOC (824)
Green (1)
Final

# SOC216H5 Study Guide - Final Guide: Collectively Exhaustive Events, Snowball Sampling, Random Variable

, Fall 2012
5 pages124 viewsFall

Department
Sociology
Course Code
SOC216H5
Professor
Green
Study Guide
Final

This preview shows page 1. to view the full 5 pages of the document.
Stratified sampling:
In statistics, stratified sampling is a method of sampling from a population.
In statistical surveys, when subpopulations within an overall population vary, it is advantageous to
sample each subpopulation (stratum) independently. Stratification is the process of dividing
members of the population into homogeneous subgroups before sampling. The strata should be
mutually exclusive: every element in the population must be assigned to only one subpopulation.
The subpops should also be collectively exhaustive: no population element can be excluded.
Then simple random sampling or systematic sampling is applied within each stratum. This often
improves the representativeness of the sample by reducing sampling error. It can produce
a weighted mean that has less variability than the arithmetic mean of a simple random sample of the
population.
Snowball Sampling:
Snowball sampling is a non-probability sampling technique where existing study subjects recruit
future subjects from among their acquaintances. Thus the sample group appears to grow like a
rolling snowball. As the sample builds up, enough data is gathered to be useful for research. This
sampling technique is often used in hidden populations which are difficult for researchers to access;
example populations would be drug users or sex workers. As sample members are not selected from
a sampling frame, snowball samples are subject to numerous biases. For example, people who have
many friends are more likely to be recruited into the sample.
Dependent variable:
The easy mnemonic to remember is that the dependent variable depends on the independent variable.
Independent variables are the things you change in your experiment. In your example that would be the
solution the egg is in.
Dependent variables are the things you measure that change in response to what you have done (the
independent variables). Generally, the dependent variables are the things you are measuring. In your
example they would be your observations. For instance, you might measure the thickness of the egg shell
3 days after exposure. Then 'shell thickness' would be your dependent variable, as it DEPENDS on the
solution you put the egg in.
Regression to the mean is the technical term for things evening out. Specifically, it refers to the
tendency of a random variable that is highly distinct from the norm to return to "normal."
For example, if a researcher gave a large group of people a test of some sort and selected the top-
performing 5%, these people would be likely to score worse, on average, if re-tested. Similarly, the bottom

Unlock to view full version

Only page 1 are available for preview. Some parts have been intentionally blurred.

5% would be likely to score better on a retest. In either case, the extremes of the distribution are likely to
"regress to the mean" due to simple luck and natural random variation in the results.
Unobtrusive measures:
Unobtrusive measures are measures that don't require the researcher to intrude in the research
context. Direct and participant observation requires that the researcher be physically present.
This can lead the respondents to alter their behavior in order to look good in the eyes of the
researcher. A questionnaire is an interruption in the natural stream of behavior. Respondents can
get tired of filling out a survey or resentful of the questions asked.
Unobtrusive measurement presumably reduces the biases that result from the intrusion of the
researcher or measurement instrument. However, unobtrusive measures reduce the degree the
researcher has control over the type of data collected. For some constructs there may simply not
be any available unobtrusive measures.
Three types of unobtrusive measurement are: indirect measures, content analysis, and secondary
analysis of data.
Ethnography is a research method designed to explore cultural phenomena where the researcher
observes society from the point of view of the subject of the study. An ethnography is a means to
represent graphically and in writing the culture of a group. The resulting field study or a case
report reflects the knowledge and the system of meanings in the lives of a cultural group. Often
considered a methodology rather than a method which means it’s a collection of methods that are
tied together by an underlying theoretical orientation.
In anthropology and other fields, a thick description of a human behavior is one that explains
not just the behavior, but its context as well, such that the behavior becomes meaningful to an
outsider. Used to establish the transferability of a qual study thought the detailed notes of a
researcher.
Discourse analysis is a general term for a number of approaches to analyzing written, vocal, or
sign language use or any significant semiotic event.
The objects of discourse analysis—discourse, writing, conversation, communicative event—are
variously defined in terms of coherent sequences of sentences, propositions, speech, or turns-at-
talk. Contrary to much of traditional linguistics, discourse analysts not only study language use

Unlock to view full version

Only page 1 are available for preview. Some parts have been intentionally blurred.

Unlock to view full version

Only page 1 are available for preview. Some parts have been intentionally blurred.

Unlock to view full version

Only page 1 are available for preview. Some parts have been intentionally blurred.