Research Methods Chapter 5: Sampling Design

<p>False (B)</p> Signup and view all the answers

<p>Both Accuracy and Precision (D)</p> Signup and view all the answers

<p>Population variance, desired precision, small error range, confidence level, and number of subgroups (A)</p> Signup and view all the answers

<p>Deception, Incentives, Quality</p> Signup and view all the answers

<p>Convenience Sampling (B)</p> Signup and view all the answers

<p>A list containing all the elements of the target population.</p> Signup and view all the answers

<p>It provides an unbiased estimate of population parameters if done correctly, is more efficient than simple random, has the lowest cost per sample, and is easier to do without a list.</p> Signup and view all the answers

<p>Increased error if subgroups are selected at different rates, especially expensive if creating strata is necessary, and high cost.</p> Signup and view all the answers

<p>It is difficult to generalize findings to the overall population, can result in biased results, and can limit the scope of the study.</p> Signup and view all the answers

<p>It can be subjective, prone to bias in selection, and can affect the accuracy of the research findings.</p> Signup and view all the answers

<p>It can be difficult to ensure accurate representation of the population, can lead to biased results if quotas are not properly set, and can be time-consuming to implement.</p> Signup and view all the answers

<p>It can lead to limited generalizability of results due to its focus on a specific network, can produce biased results if the network does not represent the broader population, and can be challenging to assess the representativeness of the sample.</p> Signup and view all the answers

<p>The difference between the sample statistic and the true population parameter.</p> Signup and view all the answers

<p>A Census attempts to include every member of the target population, while a sample is a subset of the population.</p> Signup and view all the answers

<p>Availability of elements, greater speed, lower cost, greater accuracy.</p> Signup and view all the answers

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A complete and accurate list of every element in the population.

A list of cases that are easily accessible or convenient to collect data from.

A list of cases selected based on the researcher's judgment or expertise.

A list of cases where the researcher divides the population into subgroups and then samples cases from each subgroup.

A list of cases where the researcher selects a random starting point and then chooses every kth case from the sample frame.

A list of cases where the researcher splits the population into smaller clusters and then randomly selects clusters to participate.

A list of cases where the researcher first uses one type of sampling method and then uses another method to choose a subsample from the initial sample.

A list of cases where the researcher chooses participants through recommendations from existing participants.

A list of cases where the researcher sets quotas for each subgroup and stops collecting data once the quotas are met.

The process of selecting a subset of a population to represent the characteristics and behaviors of the entire population.

The characteristics or properties of the population that are of interest to the researcher.

The specific unit of analysis in a study.

The entire group of individuals or items that the researcher is interested in studying.

The difference between a sample statistic and the corresponding population parameter.

The error caused by factors other than sampling, such as nonresponse, measurement errors, or data processing errors.

A list of elements that have been chosen to represent a target population.

The variation in a statistical measure across different samples of the same size.

A statistical measure that represents the range of values within which the true population parameter is likely to fall.

The level of certainty that the true population parameter falls within the confidence interval.

A type of sampling where every element in the population has an equal chance of being selected for the sample.

A type of sampling where the probability of selecting an element for the sample is not known.

A method of sampling where the researcher divides the population into subgroups based on specified characteristics and then samples proportionately from each subgroup.

A method of sampling where the researcher divides the population into subgroups based on specified characteristics but samples disproportionately from each subgroup.

A method of sampling where the researcher selects a random starting point and then chooses every kth case from the population list.

A method of sampling where the researcher selects a random starting point and chooses every kth case from the list.

A method of sampling where every element in the population has an equal chance of being selected.

The error caused by the variation between sample statistics and population parameters.

The accuracy of a sample in representing the true population parameter.

The extent to which a sample truly reflects the target population.