Social Works Practice Res I Population and Sampling
Study Notes
Social Work Practice Research I – Week 9 Discussion 1
Topic: Population and Sampling
1. Introduction
Population and Sampling: Central concepts in research methodology.
Population: The entire group of individuals, events, or objects that meet specific criteria for a study.
Sample: A subset of the population selected for actual study.
Importance: Sampling allows researchers to make inferences about populations without studying every member.
Relevance to Social Work: Ensures research findings are representative, ethical, and applicable to diverse communities.
2. Defining Population
Target Population: The group to which researchers want to generalize findings.
Accessible Population: The portion of the target population available for study.
Characteristics: Defined by inclusion/exclusion criteria (e.g., age, gender, location, condition).
Examples in Social Work:
All foster children in a country (target).
Foster children in one city accessible to researchers (accessible).
3. Defining Sampling
Sampling: The process of selecting a subset of the population for study.
Purpose:
Efficiency: Studying a sample saves time and resources.
Accuracy: Proper sampling ensures representativeness.
Feasibility: Populations are often too large to study in entirety.
Outcome: Enables generalization of findings to the larger population.
4. Sampling Frame
Definition: A list or representation of all elements in the accessible population.
Examples: School enrollment lists, hospital records, census data.
Importance: Ensures sample selection is systematic and unbiased.
Challenges: Incomplete or outdated frames may introduce bias.
5. Types of Sampling
a) Probability Sampling
Definition: Every member of the population has a known chance of selection.
Types:
Simple Random Sampling: Equal chance for all members.
Systematic Sampling: Selecting every nth member from a list.
Stratified Sampling: Dividing population into subgroups (strata) and sampling proportionally.
Cluster Sampling: Selecting groups (clusters) and studying all or some members.
Strengths: Representative, allows statistical inference.
Limitations: Requires complete sampling frame, may be resource‑intensive.
b) Non‑Probability Sampling
Definition: Not all members have a known chance of selection.
Types:
Convenience Sampling: Selecting easily accessible participants.
Purposive Sampling: Selecting participants based on researcher judgment.
Snowball Sampling: Participants recruit others, useful for hidden populations.
Quota Sampling: Ensuring sample meets certain quotas (e.g., gender, age).
Strengths: Practical, useful for exploratory research.
Limitations: Less representative, limited generalizability.
6. Sample Size
Importance: Larger samples increase accuracy and reliability.
Factors Influencing Size:
Population size.
Desired confidence level.
Margin of error.
Resources available.
Rule of Thumb: Balance between statistical power and feasibility.
7. Sampling Error
Definition: Difference between sample results and true population values.
Causes: Random variation, bias in selection, measurement errors.
Minimization: Use probability sampling, increase sample size, ensure accurate instruments.
Implications: Sampling error must be acknowledged in reporting.
8. Representativeness
Definition: Extent to which sample reflects characteristics of population.
Importance: Ensures findings can be generalized.
Strategies: Use stratified sampling, random selection, adequate sample size.
Challenges: Hard to achieve in diverse or hidden populations.
9. Ethical Considerations
Equity: Ensure fair inclusion of diverse groups.
Consent: Participants must agree to be part of sample.
Confidentiality: Protect identities and data.
Avoid Exploitation: Do not overburden vulnerable populations.
Transparency: Clearly explain sampling methods in reports.
10. Case Example
Study: Evaluating effectiveness of community mental health programs.
Population: All clients in mental health programs nationwide.
Accessible Population: Clients in one city.
Sampling Method: Stratified random sampling by age and gender.
Outcome: Representative sample ensures findings can inform national policy.
11. Challenges in Population and Sampling
Access Issues: Difficulty reaching certain populations.
Hidden Populations: Groups like undocumented migrants or stigmatized communities.
Resource Constraints: Limited funding and time.
Bias: Overrepresentation or underrepresentation of groups.
Dynamic Populations: Populations that change rapidly over time.
12. Strategies to Address Challenges
Community Engagement: Build trust with participants.
Adaptive Sampling: Use snowball or purposive methods for hidden groups.
Technology Tools: Use digital surveys and databases.
Pilot Studies: Test sampling methods before full implementation.
Transparency: Report limitations and biases honestly.
13. Contemporary Issues
Big Data: Expands sampling possibilities but raises privacy concerns.
Globalization: Requires cross‑cultural competence in sampling.
COVID‑19 Pandemic: Highlighted need for remote and adaptive sampling.
Intersectionality: Sampling must reflect overlapping identities.
Open Science Movement: Promotes transparency in sampling and reporting.
14. Implications for Social Work Practice
Evidence‑Based Interventions: Representative samples ensure findings apply to practice.
Policy Advocacy: Sampling informs systemic reforms.
Community Empowerment: Inclusive sampling engages diverse voices.
Professional Growth: Enhances research literacy among social workers.
Ethical Responsibility: Ensures accountability to participants and society.
15. Conclusion
Population and sampling are foundational to research methodology.
Proper sampling ensures validity, reliability, and generalizability of findings.
Probability sampling offers representativeness; non‑probability sampling provides practicality.
Ethical and cultural considerations are central to sampling decisions.
Ultimately, effective sampling strengthens evidence‑based practice, informs policy, and empowers communities.
Quiz (15 Questions)
Multiple Choice
Which term refers to the entire group of individuals relevant to a study? a) Sample b) Population c) Sampling frame d) Cluster
Which sampling method ensures every member has an equal chance of selection? a) Convenience sampling b) Purposive sampling c) Simple random sampling d) Snowball sampling
Which type of sampling is most useful for hidden populations? a) Stratified sampling b) Snowball sampling c) Systematic sampling d) Cluster sampling
Which factor does NOT influence sample size? a) Confidence level b) Margin of error c) Researcher bias d) Resources available
Which ethical principle requires protecting participant identities? a) Consent b) Confidentiality c) Equity d) Transparency
True/False
Sampling error refers to differences between sample results and true population values. (True)
Non‑probability sampling always guarantees representativeness. (False)
Stratified sampling divides population into subgroups before selection. (True)
Larger sample sizes generally increase accuracy and reliability. (True)
Dynamic populations are easy to sample consistently. (False)
Short Answer
Define population in the context of social work research.
Provide one example of probability sampling and one example of non‑probability sampling.
Identify two challenges in sampling hidden populations.
Describe one strategy to minimize sampling error.
How can inclusive sampling empower communities in social work practice?
Social Works Practice Res I- week 9 discussion 1
Population and Sampling
Probability and nonprobability are the two general categories of sampling. Probability sampling uses random selection, whereas nonprobability sampling does not. For example, if you wanted to study the effects of divorce on the psychological development of adolescents, you could gather a population of a certain number of adolescents whose parents were divorced. Then, out of that population, you could randomly select 25 of those people. If you wanted to use nonprobability sampling, you would choose specific people who had met predetermined criteria. Consider your own proposed study: Which of these sampling techniques might be best for your purposes?
In this Discussion, you identify the population, sample, and sampling technique for your study. You then consider ethical or cultural issues related to the population that you should address.
.
BY DAY 3 (Please write out the sub headings)
To Prepare:
Review the Learning Resources on sampling in research and on ethics related to vulnerable populations.
By Day 4
Post a response to the following:
In this Discussion, you identify the population, sample, and sampling technique for your study. You then consider ethical or cultural issues related to the population that you should address.
Please use the Learning Resources and the NASW Code of Ethics to support your post (i.e., cite and reference).
Please write out the sub headings)
Support your post with examples from the course text and any other resources used to respond to this Discussion. Demonstrate that you have completed the required readings, understand the material, and are able to apply the concepts. Include a full reference of resources at the bottom of the post.
Course book
Research Methods for Social Workers 8TH 18
Author: Yegidis, Bonnie L.
ISBN-13: 978-0-13-451256-3
ISBN-10: 0-13-451256-1
Edition/Copyright: 8TH 18
Publisher: Allyn & Bacon, Inc.
Publication Manual of the American Psychological Association (Paperback) 7TH 20
Author: American Psychological Association
ISBN-13: 978-1-4338-3216-1
ISBN-10: 1-4338-3216-X
Edition/Copyright: 7TH 20
Publisher: American Psychological Association – APA
Resources
Required Readings
Yegidis, B. L., Weinbach, R. W., & Myers, L. L. (2018). Research methods for social workers (8th ed.). Pearson.
oPage 128 (Review)
oChapter 9: Sampling Issues and Options (pp. 202–222)
Gordon, B. G. (2020). Vulnerability in research: Basic ethical concepts and general approach to reviewLinks to an external site.. The Ochsner Journal, 20(1), 34–38. https://doi.org/10.31486/toj.19.0079
U.S. Department of Health and Human Services, Office for Human Research Protections. (2018, January 15). The Belmont report: Ethical principles and guidelines for the protection of human subjects of researchLinks to an external site.. https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/read-the-belmont-report/index.html
Walden University Office of Research and Doctoral Services. (n.d.). Red flag issues that should trigger a research ethics consultation with the Institutional Review BoardLinks to an external site.. https://academicguides.waldenu.edu/research-center/research-ethics/red-flags
Document: Research Proposal Template (Word document)
Required Media
Optional Resources
Sankaré, I. C., Bross, R., Brown, A. F., del Pino, H. E., Jones, L. F., Morris, D. M., Porter, C., Lucas, W. A., Vargas, R., Forge, N., Norris, K. C., & Kahn, K. L. (2015). Strategies to build trust and recruit African American and Latino community residents for health research: A cohort studyLinks to an external site.. CTS: Clinical & Translational Science, 8(5), 412–420. https://doi.org/10.1111/cts.12273
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