Research Methods Chapter 5: Sampling Design

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Questions and Answers

What are the six tasks that comprise sampling design?

Define Target Population & Case, Define Population Parameters, Define Number of Cases, Define & Evaluate Sample Frames, Define Sampling Method, Define Data Security Protocols

Define Target Population & Case, Define Population Parameters, Define Sample size, Define & Evaluate Sample Frames, Define Sampling Method, Define Selection & Recruiting Protocols

Define Target Population & Case, Define Population Parameters, Define Number of Cases, Define & Evaluate Sample Frames, Define Sampling Method, Define Selection & Recruiting Protocols (correct)

Define Target Population & Case, Define Population Parameters, Define Number of Cases, Define & Evaluate Sample Frames, Define Sampling Method, Define Cases

What are the two categories of sampling methods?

Stratified and Cluster

Simple and Complex

Probability and Nonprobability (correct)

Random and Systematic

Which of the following is NOT a type of probability sampling?

Systematic

Convenience (correct)

Stratified

Simple Random

A census is always more accurate than a sample.

False Signup and view all the answers

Which of these is a characteristic of a valid sample?

Both Accuracy and Precision Signup and view all the answers

What factors can influence the decision to use a larger sample?

Population variance, desired precision, small error range, confidence level, and number of subgroups Signup and view all the answers

What are some ethical issues related to Sampling Design?

Deception, Incentives, Quality Signup and view all the answers

Which of the following is an example of a nonprobability sampling method?

Convenience Sampling Signup and view all the answers

Define a Sample Frame.

A list containing all the elements of the target population. Signup and view all the answers

What are the main advantages of Cluster sampling?

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. Signup and view all the answers

What are the main disadvantages of Stratified sampling?

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

What are the main disadvantages of Convenience sampling?

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

What are the main disadvantages of Judgment sampling?

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

What are the main disadvantages of Quota sampling?

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. Signup and view all the answers

What are the main disadvantages of Snowball sampling?

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. Signup and view all the answers

What is the basic concept of sampling error?

The difference between the sample statistic and the true population parameter. Signup and view all the answers

What is the difference between a Census and a Sample?

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

Mention four reasons why researchers prefer to use a Sample instead of a Census?

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

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Study Notes

Chapter 5: Sampling Design

This chapter covers stage 2 of the research process.
Learning objectives include understanding six tasks of sampling design, sampling theory premises, characteristics of accuracy and precision for measuring sample validity, two categories of sampling methods and techniques, various sampling techniques and their usage, and ethical issues related to sampling design.
A research thought leader quote is included: "When you sample something, you're using the crutch of borrowing chords and melodies from a song that's already great, that's already stood the test of time, that's already special." -Gerald Earl Gillum (G-Eazy)

Exhibits

Exhibit 5-1 diagrams the sampling design process in the research process.
Exhibit 5-2 illustrates common target populations in business research, including people, organizations, events, objects, settings, and texts & records.
Exhibit 5-3 gives example population parameters for a Metro U dining study, including data levels and measurement scales.
Exhibit 5-4 describes the different data types and characteristics (Nominal, Ordinal, Interval, & Ratio).
Exhibit 5-5 highlights sources of error (Sampling and Non-sampling). It outlines why sample estimates are not always population parameters, identifying errors in sampling methods, Measurement instruments, and Behavioral effects.
Exhibit 5-6 details the various types of sampling designs.
Exhibit 5-7 demonstrates how to choose a random sample using a random number table. This includes the steps of assigning numbers to elements, choosing a starting point, and determining how the numbers relate to the desired sample size.
Exhibit 5-8 compares stratified and cluster sampling methods. Stratified sampling divides the population into subgroups, ensuring homogeneity within and heterogeneity between subgroups, randomly selecting cases within each subgroup. Cluster sampling similarly divides the population but has fewer cases in each subgroup and is often selected to reduce costs.
Exhibit 5-9 compares different probability sampling designs. Designs are broken down in terms of cost, description, and advantages/disadvantages. Designs include: Simple Random, Systematic, Stratified, Cluster, and Double.
The different slides have examples of different sampling types and how to use them in different situations.

Snapshots, CloseUps, & PicProfiles

This section discusses how to avoid and correct for problem participants in research (e.g., non-compliers, frequent repeaters, fakes, liars, rush throughs, and straightliners).
It also describes how Nielsen recruits TV families. Methods include letter of invitation, special website, comprehension quizzes.
Mixed access recruitment also explores methods like computer and phone recruiting to achieve both coverage and non-sampling error reductions.

PulsePoint and Discussions

This section contains learning objectives for the chapter and a statistic on the average number of text messages per day by 18-24 year olds.

Case Discussion

This section is similar to a PulsePoint, but with focus on case examples and more in-depth discussions or learning objectives.

Learning Objectives and Chapter Outline

This outlines the six tasks of sampling design, with a thorough description/details of each.

Sampling Design in Research Process

This slide displays a flowchart emphasizing the steps in the sampling design procedure.

Accessibility Content: Text Alternatives for Images

This describes and contextualizes visual information that's used within the presentation.

Additional Topics

Milk Market Research: The chapter discusses the need for a turnaround for the milk market caused by almond- and soy-based alternatives.
Metro U Dining Study: Population parameters for a Metro U dining study. Different measures of parameters are explained.
Sample Frame: This section details the creation and importance of a sample frame (i.e., list of all population elements). Problems include incompleteness, outdated info, or inappropriateness.
Communities: Characteristics of communities who participate in research as a sample frame. Characteristics include engaging, loyal employees, digitally aware, want to share diverse interests & ideas (private and public).

Appendix

Appendix 1 calculates the sample size, while Appendix 2 serves the same function.

Additional Topics

Standard Error of Mean: The presentation explains the effect on the Standard error of mean of increasing precision in different ways.
Confidence Levels and the Normal Curve: Normal bell curves and confidence levels are explained. In the normal curve, 68% of the data falls between 1 standard deviation above and below the mean. 95% of data is within 2 standard deviations.
Metro U Comparison of Population Distribution, Sample Distribution, and Distribution of Sample Means: A comparison of population, sample, and sample mean distributions is detailed. Distribution of means appears as a normal curve with no skew, with 68% of the area in a 1x standard error range. Part C is a sample distribution made of rectangles that make up a slightly right-skewed bell curve.
Metro U Estimates Associated with Various Confidence Levels: Examples of different interval ranges for Metro, U estimates and associated confidence levels are listed. Interval ranges that reflect 68% confidence fall between 9.48 – 10.52 to 8.44 – 11.56.
Ethical Issues: The topic of ethical issues related to deception, incentives, and quality are addressed.
Key Terms (various pages): Introduces key terms related to sampling including but not limited to examples of sampling errors, non sampling errors, population parameters, etc.

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Description

Explore the intricacies of sampling design in research through this quiz. Understand key tasks, sampling methods, and ethical considerations that affect sample validity. Engage with diagrams and examples to solidify your comprehension of the topic as outlined in Chapter 5.