Question 1

A large sample is probably more representative than a small sample.

Accepted Answer

A larger sample size usually has less bias and variability, and therefore is more likely to accurately represent the population being studied.

Question 2

Simple random sampling guarantees that the sample will be representative of the population.

Accepted Answer

Simple random sampling does not guarantee that the sample will be representative of the population, as it relies on chance and can still result in a biased sample if there is significant variability within the population.

Question 3

Although proportionate stratified sampling involves selecting individuals from predetermined subgroups of the population,it does not guarantee that each subgroup in the sample will have a large number of individuals.

Accepted Answer

Proportionate stratified sampling aims to select individuals from specific subgroups based on their prevalence in the population. However, the sample size from each subgroup may not necessarily be large depending on the overall sample size and the size of each subgroup in the population.

Question 4

There is a strong possibility that a convenience sample will be biased.

Accepted Answer

Convenience sampling involves selecting participants who are readily available or easy to access, such as those who happen to be present at a certain location or who respond to an online survey. This can result in a biased sample because it may not accurately represent the population being studied. Those who are more likely to participate in the convenience sample may have different characteristics or perspectives than those who are not included, leading to inaccurate or skewed results.

Question 5

If the goal of a research study is to describe and compare different subgroups in a known population,the best strategy is to use stratified random sampling.

Accepted Answer

Stratified random sampling is a technique used to ensure representation of different subgroups in a known population. By dividing the population into strata (subgroups) and then randomly sampling from each stratum, researchers can ensure that the sample is representative of each subgroup and can accurately describe and compare them. Therefore, stratified random sampling is the best strategy for achieving the goal of describing and comparing different subgroups in a population.

Question 6

If a researcher wants a sample to accurately represent the composition of the population,the best strategy is to use stratified random sampling.

Accepted Answer

The answer of If a researcher wants a sample to...

Question 7

Describe the basic distinction between probability sampling and nonprobability and explain why most psychology research uses nonprobability methods.

Accepted Answer

The answer of Describe the basic distinction between probability sampling...

Question 8

Stratified random sampling is used instead of simple random sampling when a researcher wants to ensure that the sample has specified characteristics.

Accepted Answer

Stratified random sampling involves dividing the population into subgroups based on specific characteristics and then selecting a random sample from each subgroup. This ensures that the sample represents the characteristics of the population as a whole.

Question 9

When a researcher does not know the exact number of individuals in the population,it is necessary to use a nonprobability sampling method.

Accepted Answer

Nonprobability sampling methods are often used when the population is unknown or cannot be accurately measured. These methods do not use random selection, so they are not suitable for obtaining representative samples of the population.

Question 10

The most commonly used sampling methods in psychology are nonprobability sampling methods.

Accepted Answer

Nonprobability sampling, such as convenience sampling or snowball sampling, are often used in psychology research due to practical, ethical, or financial constraints. Probability sampling methods, such as random sampling or stratified sampling, are less commonly used due to their more rigorous procedures and requirements.

Question 11

It is always necessary to have at least 25-30 participants in a study.

Accepted Answer

The necessary number of participants in a study can vary depending on the research question, study design, statistical power, and other factors. In some cases, a smaller sample size may be appropriate, while in others, a larger sample may be needed.

Question 12

Convenience sampling involves selecting individuals who are easy to get.

Accepted Answer

Convenience sampling involves selecting individuals who are easily accessible or available, which may not provide a representative sample of the population.

Question 13

One requirement for a simple random sample is that the likelihood of selecting one specific individual does not depend on which other individuals are selected for the sample.

Accepted Answer

This is one of the key characteristics of a simple random sample. Each individual in the population must have an equal chance of being selected for the sample, without being influenced by the selection of other individuals.

Question 14

Selection bias is likely to produce a sample with characteristics that are noticeably different from those in the population.

Accepted Answer

Selection bias occurs when the selection of individuals for a study or sample is not random and is influenced by certain characteristics or factors. This can result in a sample that is not representative of the population and may have different characteristics.

Question 15

Simple random sampling without replacement means that the likelihood of selecting one specific individual will depend on which other individuals are selected for the sample.

Accepted Answer

Simple random sampling without replacement means that each individual in the population has an equal chance of being selected for the sample, but once an individual is selected, they are removed from the population and cannot be selected again. Therefore, the likelihood of selecting one specific individual will depend on which other individuals have been selected for the sample.

Question 16

Stratified random sampling and quota sampling are both classified in the category of probability sampling techniques.

Accepted Answer

Stratified random sampling is a probability sampling technique where the population is divided into different subgroups or strata, and samples are randomly selected from each stratum. Quota sampling, on the other hand, is a non-probability sampling technique where the sample is chosen to reflect certain characteristics of the population, but not randomly.

Question 17

If you cannot list all the individuals in the population,then you cannot take a simple random sample.

Accepted Answer

Simple random sampling requires a complete list of individuals in the population, from which random samples can be drawn. If such a list is not available or cannot be compiled, simple random sampling cannot be used.

Question 18

Using a simple random sample eliminates bias from the selection process.

Accepted Answer

A simple random sample is a method of selecting a subset of individuals from a larger population in which every individual has an equal chance of being selected. This eliminates bias from the selection process as all individuals have an equal probability of being chosen.

Question 19

Stratified and proportionate stratified sampling both involve selecting individuals from predetermined subgroups in the population.

Accepted Answer

Both stratified and proportionate stratified sampling involve dividing the population into predetermined subgroups and selecting individuals from each subgroup. The difference between the two is the way the sample is selected from each subgroup. In stratified sampling, a set number of individuals is selected from each subgroup, while in proportionate stratified sampling, the number of individuals selected from each subgroup is based on the proportion of individuals in that subgroup in the population.

Question 20

When a researcher does not know the exact number of individuals in the population but still wants to control the composition of a sample,the best technique is to use quota sampling.

Accepted Answer

Quota sampling allows the researcher to ensure that the sample represents certain characteristics of the population, even if the exact number of individuals in the population is unknown. The researcher sets quotas based on certain demographic or other characteristics and then selects participants until the quotas are filled.

Quiz 5: Selecting Research Participants