Question 1

The summary description of a given variable in the sample is called a sample statistic.

Accepted Answer

A sample statistic is a summary measure of a variable computed from a sample, rather than the entire population. It provides information about the central tendency, variability, and distribution of the variable in the sample. Examples of sample statistics include mean, standard deviation, and proportion.

Question 2

Cluster sampling is a very efficient tool, but the efficiency means a less accurate sample because with each cluster, there is a chance for sampling error.

Accepted Answer

Cluster sampling can be less accurate than other sampling methods because it increases the chance of sampling error by grouping the population into clusters that may not represent the whole population evenly.

Question 3

Random selection permits the researcher to link findings from a sample to the body of probability theory in order to estimate the accuracy of those findings.

Accepted Answer

Random selection ensures that each member of the population has an equal chance of being included in the sample, which allows for generalization of findings to the larger population and estimation of the accuracy of those findings using probability theory.

Question 4

A sample element is that unit about which information is collected and that provides the basis of analysis.

Accepted Answer

This statement is true. A sample element refers to the individual entity or object that is being studied in research or analysis. It is the unit of analysis and is used to draw conclusions and make inferences about a larger population or group.

Question 5

A researcher who uses a stratified sampling technique ____.

Accepted Answer

A researcher who uses a stratified sampling technique recognizes the extent that subsets that are homogeneous on stratified variables will generally result in homogeneity on other variables as well. This method helps to ensure that the sample is more representative and diverse, and can help to reduce sampling error. Options A, C, and D are incorrect because they are either not true or do not relate to the benefits of using a stratified sampling technique.

Question 6

Confidence levels allow the researcher to have some idea of how closely their samples reflect the parameter. Which statement about confidence levels is true?

Accepted Answer

A 99% confidence level typically corresponds to estimates falling within approximately 2.576 standard errors of the parameter, not three. However, the statement is closest to being true compared to the others, as it reflects a high level of confidence.

Question 7

The standard error is the measure of sampling error.

Accepted Answer

The standard error is a measure of the variability of sample estimates that are calculated from different random samples of the same population. It indicates the precision of the sample mean as an estimate of the population mean and is therefore a measure of sampling error.

Question 8

Which of the following is true concerning sampling error?

Accepted Answer

Sampling error refers to the variability between sample statistics and the corresponding population parameter due to chance. Option A is correct because the central limit theorem predicts that sample statistics will follow a normal distribution around the population parameter if many independent random samples are drawn from a population. Option B is incorrect because probability theory does allow us to estimate how closely sample statistics are clustered through the use of the standard error. Option C is also incorrect because the standard error is precisely used to estimate how far or close the sample statistics are from the population parameter. Therefore, the best answer is A.

Question 9

Which of the following is not a reason for using random selection methods in selecting samples?

Accepted Answer

Random selection methods are used to eliminate bias and ensure that the sample represents the population. Selecting cases on an intuitive basis would defeat the purpose of random selection.

Question 10

When no reasonable sampling frame exists and a probability sample cannot be drawn, at least estimates about the sample accuracy are available through nonprobability samples.

Accepted Answer

Nonprobability samples do not allow for the calculation of sampling error or estimates about sample accuracy in the same way that probability samples do, because they do not involve random selection from the population.

Question 11

When researching a population where it is impossible or impractical to compile a list of the elements, which sampling technique is appropriate to use?

Accepted Answer

When it is impossible or impractical to compile a list of elements in a population, a cluster sample is appropriate. This technique involves dividing the population into clusters or groups and then randomly selecting some of those clusters to be included in the sample. Within each selected cluster, all individuals are included in the sample. This method can be cost-effective and time-efficient, particularly when the population is large and widely dispersed, such as all residents in a particular state or country.

Question 12

A list of all elements in a population is referred to as the sampling frame.

Accepted Answer

A sampling frame is a list of all the individuals or elements in a population from which a sample can be drawn.

Question 13

Which of the following is not appropriate for use as a sampling frame?

Accepted Answer

Using a list of licensed drivers to ask juveniles their opinions about drinking prohibitions is not appropriate as the sampling frame does not accurately represent the target population.

Question 14

Sampling is often used when it is not possible to collect information from all persons you want to study and when it is not necessary to collect information from all persons.

Accepted Answer

Sampling involves selecting a subset of individuals from a larger population, which is often done when it is not feasible or necessary to collect data on every individual in the population.

Question 15

A good way to avoid sampling bias in the assessment of public opinion about a specific criminal justice topic is to employ the use of a radio call-in show.

Accepted Answer

Using a radio call-in show can lead to sampling bias because only individuals who listen to the specific radio show and are motivated to call in are represented, which may not be representative of the general public opinion about the topic. It would be better to use a random sampling method to select participants for the assessment.

Question 16

Stratified sampling results in a greater degree of representativeness, but at the same time, increases the probable sampling error.

Accepted Answer

Stratified sampling actually aims to reduce sampling error by ensuring that subgroups (strata) are adequately represented in the sample, thus increasing the representativeness and precision of the results.

Question 17

The purpose of sampling is to select a set of elements from a population so that the descriptions of the sample statistics accurately portray the parameters of the population. This is best achieved through the use of ____.

Accepted Answer

Random selection ensures that every member of the population has an equal chance of being included in the sample, reducing bias and increasing the representativeness of the sample for the population. Convenience samples may introduce bias if the sampling method is not rigorous, and sampling error refers to the inevitable discrepancies between the actual population parameter and the estimated sample statistic. The sampling element is not a commonly used concept in statistics.

Question 18

Which statement is true concerning the relationship between standard error and sample size?

Accepted Answer

There is an inverse relationship between standard error and sample size. As sample size increases, the standard error decreases, and as sample size decreases, the standard error increases. This is because as sample size increases, the sample means become closer to the true population mean, reducing the variability and therefore the standard error.

Question 19

A basic principle of probability sampling is that a sample will be representative of the population from which it is drawn if ____.

Accepted Answer

Probability sampling ensures that every member of the population has an equal chance of being selected for the sample, which helps ensure that the sample is representative of the population. Choices B and C, on the other hand, do not guarantee representativeness and may introduce biases into the sample. Choice D is incorrect because one of the options is correct, and therefore, this answer choice is not accurate.

Question 20

Systematic sample is?

Accepted Answer

Systematic sampling is a method in which every nth member of the population is selected for inclusion in the sample, and it is frequently used as a substitute for simple random sampling when it is not feasible to obtain a complete list of the population. Therefore, option C is the correct choice. Option A is incorrect because systematic sampling is a type of probability sampling. Option B is incorrect because stratified sampling is different from systematic sampling. Option D is incorrect because it is a probability sampling method.

Quiz 6: Section 1: Sampling