Research Methods Ch. 5

Snowball sampling would be an effective strategy for a researcher to use if a researcher was interested in studying a population of gang members.

Periodicity is a source of sampling error in most non-probability sampling.

Findings based on a sample can be taken as representing the elements that compose the sampling frame.

Stratifying a population prior to drawing a sample:
generally occurs when the variables used to stratify are known to be associated with the dependent variable

Which of the following is a common problem that can bias what appears to be a random sample?
Both a and c
(an incomplete sampling frame and non-responsiveness)

When all elements in a population are identical:
sampling is unecessary

The individual members of the population whose characteristics are to be measured are known as:

A researcher studying small town religiosity in the United States randomly selected ten states. From these states, he randomly selected one tenth of all counties. From these counties, he randomly selected one tenth of cities with populations smaller than 10,000. From these towns, he obtained lists of all houses of worship and randomly selected three. From these, he selected ten practitioners to be interviewed. In this example, which is not a cluster?

The population is the entire set of individuals or other entities to which study findings are to be generalized.

Another name for convenience sampling is:
availability sampling

A subset of the population used to study the population as a whole is known as a(n):

In a situation of perfect homogeneity there is little need to be concerned with careful sampling procedures.

In a census, the probability of selection is always less than 1.0.

Every kth element in a list is chosen for inclusion in the sample in:
systematic sampling

Field researchers are often interested in studying deviant cases in order to improve their understanding of the more typical pattern.

In terms of probability theory, the standard error is valuable because:
it indicates the extent to which the sample estimates will be distributed around the population parameter

Dr. Smith is instructing his graduate students to put together a sample for an upcoming research study of college students. The graduate students were asked to stand outside of the student union to solicit participants, finding 50 freshmen, 50 sophomore, 50 juniors, and 50 seniors. What sort of sampling method is being used?
quota sampling

A study population is:
that aggregation of elements from which the sample is actually selected

A researcher gets a list of all 500 members of Social Club Z that she wants to include in her study. She only has the funding and time to survey 50 members. She takes her list of members, randomly selects a starting point, and then selects every tenth name from the list to be included in her sample. In this example, the sampling interval is:

As the size of the sample goes up:
so does confidence in its representativeness of the sample

A researcher who uses a list of registered voters as a sampling frame, and selects every 5th person on the randomized list is engaging in what kind of sampling?

The individual members of the population whose characteristics are to be measured are called the sample.

Non-probability sampling:
denies the researcher the use of statistical theory to estimate the probability of correct inferences

Field researchers are often interested in studying deviant cases in order to improve their understanding of the more typical pattern

Cluster sampling is a type of sampling in which elements are selected in two or more stages, with the first stage being random selection of naturally occurring clusters.

Probability samples are advantageous to the researcher because:
the method by which they are selected limits conscious and unconscious sampling bias and the accuracy or representativeness of the sample can be estimated

Which of the following is false about a random probability sample?
elements are chosen haphazardly

A target population refers to a set of elements larger than or different from the population sampled and to which the researcher would like to generalize study findings.

Drawing a judgmental sample:
allows researchers to use their prior knowledge about the population

Stratification represents a modification to rather than an alternative to simple random sampling and systematic sampling.

A confidence interval at the 68% confidence level will be larger than one constructed at the 95% confidence level.

If a population were perfectly homogeneous, a single case could represent the entire population.

In purposive sampling, interviews should continue until a saturation point is reached.

Generally, the more heterogeneous the population, the more beneficial it is to use stratified sampling.

When cases are chosen not to represent the population but because of an interesting outcome, we refer to this as sampling the independent variable

Simple random sampling is the most effective way to further understand uncommon populations