Learn how to draw the right sample to reach your target audience.
One of the most important questions to answer when designing research is, “What group(s) of people does the business need to understand in order to make an informed decision about the issue at hand?” In the language of sampling, these people are the “target population.” Sampling is the means of specifying how the members of a population will be selected for study. It is essential that the sample be representative of the target population, that is, a microcosm in terms of demographic, attitudinal, and behavioral characteristics. If the sample is not representative, conclusions from the research will be biased and any insights developed incorrect. Guidance from non-representative samples will be irrelevant or, at worst, harmful to the business.
Graduates receive University of Georgia continuing education units (CEUs) as well as a digital badge.
After completing this course you should be able to:
- Explain how sampling works. Speak knowledgeably about margin of error and confidence level, so that you can determine statistically significant findings, and understand the importance of base size.
- Discuss the sampling design process: definition of the target population, best modes to reach that population, determination of the sampling frame, selection of sampling technique(s), determination of sample size, and execution of the sampling process.
- Explain the differences between probability and non-probability samples, the benefits, drawbacks, and when each might be used.
- Discuss the major types of probability sampling (simple random, systematic, stratified, and cluster), their benefits, drawbacks, and when each might be used.
- Discuss the major types of non-probability sampling (convenience, quota, and snowball), their benefits, drawbacks, and when each might be used.
- Explain the differences between landline and mobile phone sampling
- Describe sampling techniques and sources specific to Internet data - collection, including mobile research.
- Discuss the survey assignment process and understand the potential bias implications of routing, targeting, prescreening, and prior survey exposure.
- Describe the concept of consistent sampling both in terms of a consistent sample frame and how sample is drawn and quotas are set against that frame.
- Discuss how a single sample frame is not necessarily connected to a single mode and that having multiple points of contact for the same person can increase response rates.
- Describe how the screener section of the survey, as well as dropouts, data quality, and technical issues, will ultimately impact the “sample” that completes the survey.
- Describe the challenges in obtaining representative samples and how representative samples can be improved at the selection stage or through weighting.
- Describe when to use margin of error calculations and confidence levels of reporting results.
- Explain how to use the principles of sampling to make judgments about representativeness and bias in secondary data.
- Describe the challenges researchers face when developing samples for international studies.
- Identify the ethical considerations in sampling as applied to both end users (“clients”) and participants.
Keith Phillips – Senior Methodologist, Research Now SSI
Keith is the Senior Methodologist in Research Now SSI’s Knowledge department. Keith’s role at SSI includes conducting primary research projects, helping clients with the research issues they face on a day to day basis, training colleagues, and working to support company-wide sampling initiatives. Prior to joining SSI in March of 2010, Keith was a Senior Research Manager in the Motion Picture Division of OTX Research, which he joined in 2004. Keith has presented webinars for the AMA, ARF, AAPOR, ESOMAR, GreenBook, and Quirk’s. He has presented live at AAPOR, ARF Rethink, and ESOMAR Congress among others.
Anticipated course release in early 2018.
Details are subject to change without notice.