In this sampling the sample selection follows a particular set of conditions

Which of the following best defines random sampling?

a. Researchers stationing themselves at a particular location with access to parts of the population and randomly selecting those who pass by.
b. Each member having the same opportunity and probability as other members of the population to be selected for participation in a study.
c. Each member having a random probability of being selected. Not all members of the population have the same probability of being selected.
d. Researchers have more than one population of interest and sample randomly across these different populations not knowing which population they are sampling from. This helps reduce bias.

What is the main benefit of using random sampling?

a. It is the most straightforward way to obtain a representative sample.
b. It is the most straightforward way to obtain a statistically powerful sample.
c. It is the most straightforward way to obtain a sample from which the results of the study will be applicable to other populations.
d. It is the most straightforward way to recruit the largest amount of subjects.

What is the biggest barrier to using random sampling?

a. It is often unethical. You should not have all participants have equal chances of being selected because some might not want to participate.
b. It is only usable when the population is large. Thus, it is not useful for most research.
c. It is often impractical as researchers usually do not have access to the entire population of interest to recruit them randomly.
d. It is biased because the randomness makes it difficult to analyze the data that you collect.

What do alternatives to random sampling accomplish?

a. They make the sample less biased.
b. They are ways to deal with lack of accessibility to some members of the population.
c. They are non-probability samples.
d. They are ways to deal with randomness in the data that random sampling produces.

What distinguishes stratified sampling from oversampling?

a. Stratified sampling is when a researcher intentionally over-recruits members of underrepresented groups whereas oversampling is a non-probability sample.
b. Stratified sampling does not aim for a generalizable sample while oversampling does.
c. Oversampling does not aim for a generalizable sample while stratified sampling does.
d. Stratified sampling divides the population into homogeneous groups along some dimension whereas oversampling is when a researcher intentionally over-recruit underrepresented groups.

How or why does stratified sampling help with representativeness of your sample?

a. Stratified sampling produces a non-probability sample.
b. Stratified sampling divides the population into homogeneous groups and you can ensure you sample enough along that dimension of interest.
c. Stratified sampling over-recruits samples in the most inaccessible category.
d. Stratified sampling samples via participant networks. Participants help recruit and therefore you gain a representative sample.

When is non-probability sample appropriate to be used?

a. When the population is too diverse.
b. When representativeness of your sample is not important to your research.
c. When you hope to use oversampling techniques.
d. When you only need a relatively small sample.

The use of college undergraduates from introductory psychology courses in psychological research is an example of a…

a. random sample.
b. stratified sample.
c. convenience sample.
d. snowball sample.

Which of the following is not an advantage of using an online sample?

a. Collecting data is usually fast.
b. Collecting data is often cheap.
c. Collecting data is often in direct contact (i.e., in person) with the participant in a laboratory setting.
d. There is often a large pool of participant pool from which you may sample.

With regards to representing the larger population, which of the following is true?

a. Researchers initially had doubts about the representativeness of samples recruited from Mturk, but recent evidence provided by Buhrmester, Kwang, and Gosling (2011) suggest that Mturk samples surpass other internet samples and many U.S. college samples.
b. Researchers have had doubts about the representativeness of samples recruited from Mturk, and recent evidence provided by Buhrmester, Kwang, and Gosling (2011) supports the validity of that concern.
c. Researchers initially had very little, if any, doubts about the representativeness of samples recruited from Mturk, but recent evidence provided by Buhrmester, Kwang, but Gosling (2011) suggest that Mturk are not representative of the population at large.
d. Researchers initially had very little, if any, doubts about the representativeness of samples recruited from Mturk, but recent evidence provided by Buhrmester, Kwang, and Gosling (2011) suggest that Mturk samples surpass other internet samples and many U.S. college samples.

Which of the following is the best benefit of paying your participants?

a. It might change the way your participants behave on the task.
b. Incentives can interact with certain research questions that influence the validity of the research outcome.
c. Incentives can help with participant retention and recruit a more diverse sample.
d. Payments can end up being coercive if not used properly.

Which of the following is not a method of effectively identifying how much to pay your participant?

a. Use past literature that was published recently.
b. Consult with your local IRB.
c. Examine the work done by past researchers who are using a similar method in the same field.
d. Ask the participants how much they think they should be paid.

Which of the following is the best example of a nominal scale?

a. Types of chocolate bars by brand name
b. Height of children in inches
c. Temperature in degrees Celsius
d. Political conservatism on a scale from 1 to 10

Parametric tests are suitable for…

a. nominal and ordinal scales only.
b. nominal scales only.
c. interval and ratio scales only.
d. ratio scales only.

Which of the following is true with regards to parametric and non-parametric tests?

a. Parametric tests make more assumptions than non-parametric tests, and can only be used on nominal data.
b. Parametric tests make fewer assumptions than non-parametric scales, and can only be used on interval and ratio tests.
c. Non-parametric tests are preferred over parametric tests, particularly because they can be applied to a wider range of measurement scales.
d. Parametric and non-parametric tests can be used on the same types of measurement scales. Which you use depends entirely on your research question.

In the context of measurement, reliability refers to the extent to which ________________________ whereas validity refers to the extent to which ________________________.

a. measures yield consistent results; measures capture what they are intended to measure
b. measures capture what they are intended to measure; measures yield consistent results
c. participants can understand the measures; participants can accurately respond to the measures
d. researchers can obtain the same results with the same measure; the measures can be used to more than one population

Statistical power refers to the __________________; given that __________________.

a. probability of detecting an effect; the researcher has a representative sample
b. probability of not detecting an effect; the effect is false
c. probability of detecting an effect; an effect exists
d. probability of detecting an effect; measurement error is minimized

Which of the following reasons below is not one that describes the importance of formulating an analysis plan before you collect data?

What sampling method is used when participants are selected according to a criteria set?

What is the sample method of selection?

Which sampling design is based on the selection of individuals according to the criteria set by the researcher?

What is the type of sampling procedure wherein the participants are grouped according to a set of criteria specified in a research?