1. 1 MARKETING RESEARCH Week 3 Session A IBMS Term 2, 2008-09

2. 2 Today: 2 x Lectures 2 x Project Sessions Project Brief Due – Fri 13 th Mar Questionnaire Due – Fri 20 th Mar Coaching Sessions Throughout the Week (W.Moes) This Week

3. 3 Today: Lecture: Sample Selection (Ch 12) Break Lecture: Sample Selection (Ch 12) Class Activity: Review Questions & Case

4. Determining How to Select a Sample

5. 5 Basic Concepts in Sampling Population: the entire group under study as defined by research objectives Census: an accounting of the complete population (a list)

6. 6 Basic Concepts in Sampling Sample: a subset of the population that should represent the entire group Sample unit: the basic level of investigation

7. 7 Basic Concepts in Sampling Sampling error: any error in a survey that occurs because a sampling is used –Selection problems –Incorrect sample size A sample frame: a master list of the entire population –Telephone List –Customer List –Email List with email addresses

8. 8 Basic Concepts in Sampling Sample frame error: the sample frame fails to account for all of the population –a telephone book listing does not contain unlisted numbers –A list of visitors to the EPBS Career Beurs Stand does not include people that could not make it to the Beurs.

9. 9 REMEMBER! Two types of errors in sampling: –Sampling error –Sample frame error

10. 10 Reasons for Taking a Sample Practical considerations such as cost and population size Inability of researcher to analyze huge amounts of data generated by census Samples can produce precise results

11. 11 Two Basic Sampling Methods Probability samples: members of the population have a known chance (probability) of being selected into the sample Non-probability samples: probability of selecting members from the population into the sample are unknown

12. 12 Probability Sampling Methods (probability is known) Simple random sampling Systematic sampling Cluster sampling Stratified sampling

13. 13 Probability Sampling Methods

14. 14 Probability Sampling: Simple Random Sampling Simple random sampling: the probability of being selected into the sample is “known” and equal for all members of the population –E.g., Blind Draw Method –Random Numbers Method

15. 15 Probability Sampling: Simple Random Sampling –Advantage: Known and equal chance of selection –Disadvantages: Complete accounting of population needed Cumbersome to provide unique designations to every population member

16. 16 Probability Sampling Systematic Sampling Systematic sampling: way to select a random sample from a directory or list that is much more efficient than simple random sampling –Skip interval=population list size/sample size

17. 17 Probability Sampling Systematic Sampling –Advantages: Approximate known and equal chance of selection…it is a probability sample plan Efficiency…do not need to designate every population member Less expensive…faster than SRS –Disadvantage: Small loss in sampling precision

18. 18 Probability Sampling Cluster Sampling Cluster sampling: method in which the population is divided into groups, any of which can be considered a representative sample –Area sampling

19. 19 Probability Sampling Cluster Sampling –Advantage: Economic efficiency…faster and less expensive than SRS –Disadvantage: Cluster specification error…the more homogeneous the clusters, the more precise the sample results

20. 20 Stratified Sampling When the researcher knows the answers to the research question are likely to vary by subgroups…

21. 21 Stratified Sampling –Research Question: “To what extent do you value your college degree?” Answers are on a five point scale: 1= “Not valued” and 5= “Highly valued”

22. 22 Stratified Sampling

23. 23 Probability Sampling Stratified Sampling Stratified sampling: method in which the population is separated into different strata and a sample is taken from each stratum

24. 24 Probability Sampling Stratified Sampling –Advantage: More accurate overall sample of skewed population…see next slide for WHY –Disadvantage: More complex sampling plan requiring different sample size for each stratum

25. 25 Break 15 minutes

26. 26 Nonprobability Sampling With nonprobability sampling methods selection is not based on fairness, equity, or equal chance. –Convenience sampling –Judgment sampling –Referral sampling –Quota sampling

27. 27 Nonprobability Sampling May not be representative but they are still used very often. Why? –Decision makers want fast, relatively inexpensive answers… nonprobability samples are faster and less costly than probability samples.

28. 28 Nonprobability Sampling May not be representative but they are still used very often. Why? –Decision makers can make a decision based upon what 100 or 200 or 300 people say…they don’t feel they need a probability sample.

29. 29 Nonprobability Sampling Convenience samples: samples drawn at the convenience of the interviewer –Error occurs in the form of members of the population who are infrequent or nonusers of that location

30. 30 Nonprobability Sampling Judgment samples: samples that require a judgment or an “educated guess” as to who should represent the population –Subjectivity enters in here, and certain members will have a smaller chance of selection than others

31. 31 Nonprobability Sampling Referral samples (snowball samples): samples which require respondents to provide the names of additional respondents –Members of the population who are less known, disliked, or whose opinions conflict with the respondent have a low probability of being selected

32. 32 Nonprobability Sampling Quota samples: samples that use a specific quota of certain types of individuals to be interviewed –Often used to ensure that convenience samples will have desired proportion of different respondent classes

33. 33 Online Sampling Techniques Random online intercept sampling: relies on a random selection of Web site visitors Invitation online sampling: is when potential respondents are alerted that they may fill out a questionnaire that is hosted at a specific Web site

34. 34 Online Sampling Techniques Online panel sampling: refers to consumer or other respondent panels that are set up by marketing research companies for the explicit purpose of conducting surveys with representative samples

35. 35 Developing a Sample Plan Sample plan: definite sequence of steps that the researcher goes through in order to draw and ultimately arrive at the final sample

36. 36 Developing a Sample Plan 1.Define the relevant population. 2.Obtain a listing of the population. –The incidence rate is the percentage of people on a list who qualify as members of the population 3.Design the sample plan (size and method).

37. 37 Developing a Sample Plan 4.Draw the sample. –Substitution methods: Drop-down substitution Oversampling Resampling

38. 38 Developing a Sample Plan 5.Validate the sample. –Sample validation is a process in which the researcher inspects some characteristic(s) of the sample to judge how well it represents the population. 6.Resample, if necessary.

39. 39 Class Activity In your groups, draft up a sample plan for your Research Project. Submit to the teacher and then you are finished for this teaching session.