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Sampling by team

Sampling by team






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  • The researcher can consciously decide what elements to include in the sample.
  • The main assumption associated with convenience sampling is that the members of the target population are homogeneous. That is, that there would be no difference in the research results obtained from a random sample, a nearby sample, a co-operative sample, or a sample gathered in some inaccessible part of the population.

Sampling by team Sampling by team Presentation Transcript

  • Prepared By-Raman Sharda, Keshav Trehan, DevinaDeshmukh, Prashant Areker and Rahul Yadav
  • Overview1)Sample or Census2) The Sampling Design Process3)Classification of Sampling Techniques4) Internet Sampling5)Internet Sampling6)International Marketing Research7)Ethics in Marketing Research
  • Sample or Census Population- The Aggregate of all the elements, sharing some common set of characteristics, that comprise the universe for the purpose of the marketing research problem. Census- A complete enumeration ofthe elements of a population or study objects. Sample- A subgroup of the elements of the population selected for participation in the study.
  • Sample or CensusTable 11.1 Conditions Favoring the Use of Type of Study Sample Census 1. Budget Small Large 2. Time available Short Long 3. Population size Large Small 4. Variance in the characteristic Small Large 5. Cost of sampling errors Low High 6. Cost of nonsampling errors High Low 7. Nature of measurement Destructive Nondestructive 8. Attention to individual cases Yes No
  • The sampling Design ProcessDefine the Target Population Define the Sampling frame Select a Sampling Determine the Sample Size Execute the Sampling Process
  • Define the target population Target Population-The Collection of elements or object that process the information sought by the researcher and about which inference are to be made. Element- An object that possesses the information sought by the researcher. Sample Unit- The basic unit containing the elements of the population to be sampled.
  • Determine the sampling Frame Sampling Frame- A representation of elements of the target population. It consist of a list of set of directions to identify the target population.
  • Select a Sampling Technique Bayesian Approach Sampling with replacement Sampling without replacement
  • Determine the Sample Size Sample Size-The Number of Elements to be include a study. Important Qualitative Factors in Determining the Sample Size-1. Importance of the Decision2. The Nature of the Research3. The Number of variables4. The Nature of the analysis5. Sample size used in similar studies6. Incidence rates7. Completion rate and8. Resource constraint
  • Sample Sizes Used in MarketingResearch StudiesTable 11.2Type of Study Minimum Size Typical RangeProblem identification research 500 1,000-2,500(e.g. market potential)Problem-solving research (e.g. 200 300-500pricing)Product tests 200 300-500Test marketing studies 200 300-500TV, radio, or print advertising (per 150 200-300commercial or ad tested)Test-market audits 10 stores 10-20 storesFocus groups 2 groups 6-15 groups
  • Executive the Sampling Process After Selection of sampling Techniques execute the research process.
  • Types of Samples Used Sampling Techniques Non-Probability Samples Probability Samples Simple Stratified RandomJudgement Convenienc e Systematic Cluster Quota Snowball
  • NONPROBABILITY SAMPLING Most researchers are bounded by time, money and workforce and because of these limitations, it is almost impossible to randomly sample the entire population and it is often necessary to employ another sampling technique, the non-probability sampling technique. Sampling techniques that do not use chance selection procedures Rely on personal judgment of the researcher Subjects in a non-probability sample are usually selected on the basis of their accessibility or by the purposive personal judgment of the researcher This entails that the sample may or may not represent the entire population accurately
  • NONPROBABILITY SAMPLING The downside of this is that an unknown proportion of the entire population was not sampled Therefore, the results of the research cannot be used in generalizations pertaining to the entire population
  • TECHNIQUES OF NONPROBABILITYSAMPLING Convenience Sampling (Haphazard or Accidental Sampling): A nonprobability sampling technique that attempts to obtain a sample of convenient elements The selection of sampling units is left primarily to the interviewer Samples are selected because they are accessible to the researcher Often, respondents are selected because they happen to be in the right place at the right time Examples: -people in the street interviews -use of students, church groups, and members of social organizations -mall-intercept interviews without qualifying the respondents -tear-out questionnaires included in a magazine
  • TECHNIQUES OF NONPROBABILITYSAMPLING Convenience Sampling: (continue) It is considered easiest, cheapest and least time consuming Sampling units are accessible, easy to measure and cooperative Limitations of Convenience Sampling: -Many potential sources of selection bias are present, including respondent self-selection -Not representative of any definable population Hence, it is not meaningful to generalize to any population from a convenience sample Inappropriate for marketing research projects involving population inferences
  • TECHNIQUES OF NONPROBABILITYSAMPLING Convenience Sampling: (continue) Not recommended for descriptive or causal research but can be used in exploratory research for generating ideas, insights, or hypotheses They can be used for focus groups, pretesting questionnaires, or pilot studies In these cases, caution should be exercised in interpreting results This technique is sometimes used in large surveys
  • Convenience Sampling: (continue) A B C D E 1 6 11 16 21 2 7 12 17 22 3 8 13 18 23 4 9 14 19 24 5 10 15 20 25Group D happens to assemble at a convenient time and place. So all the elements in this group are selected.The resulting sample consists of elements 16, 17,18,19,20.No elements are selected from groups A,B,C and E.
  • TECHNIQUES OF NONPROBABILITYSAMPLING Judgmental Sampling (Purposive Sampling): A form of convenience sampling in which the population elements are purposely selected based on the judgment of the researcher In this type of sampling, subjects are chosen to be part of the sample with a specific purpose in mind With judgmental sampling, the researcher believes that some subjects are more fit for the research compared to other individuals This is the reason why they are purposively chosen as subjects It is low cost, convenient and quick
  • TECHNIQUES OF NONPROBABILITYSAMPLING Judgmental Sampling (Purposive Sampling): (continue) Examples: -test markets selected to determine the potential of a new product -purchase engineers selected in industrial marketing research as they are considered to be representative of the company -bellwether precincts selected in voting behaviour research -expert witnesses in court -department stores selected to test a new merchandising display system
  • Judgmental Sampling (Purposive Sampling)(continue): Limitations: -It is subjective and its value depends entirely on the researcher’s judgment, expertise and creativity -It is extremely difficult to obtain meaningful results from a judgement sample because no two experts will agree upon the exact composition of a typical sample - Therefore, in the absence of an external criterion, there is no way in which in the research results obtained from one judgement sample can be judged as being more accurate than the research results obtained from another
  • TECHNIQUES OF NONPROBABILITYSAMPLING Judgmental Sampling (Purposive Sampling) (continue): Limitations: -It may be useful if broad population inferences are not required - It does not allow direct generalization to a specific population, since the population is not defined explicitly Judgmental samples are frequently used in commercial marketing research projects in case of department store
  • Judgmental Sampling (continue) A B C D E 1 6 11 16 21 2 7 12 17 22 3 8 13 18 23 4 9 14 19 24 5 10 15 20 25 The researcher considers groups B,C and E to be typical and convenient. Within each of these groups one or two elements are selected based on typicality and convenience. The resulting sample consists of elements 8,10,11,13 & 24. No element is selected from each column or group
  • Quota Sampling Two stage restricted Judgmental Sampling  Developing control categories or quotas , of population elements  Sample elements are selected based on convenience or judgment • Dependability • Advantages
  • Snowball Sampling An initial group of respondents Objective: To estimate characteristics which are rare in population User group : Industrial buyers Advantages  Increases the likelihood of location  Relatively low sampling variance and costs
  • Uses of Non-Probability SamplingTechniques Concept test, package tests, name tests and copy test Where projections to the population are usually not needed Use of Mall-Intercept Quota Sampling
  • Probability Sampling “A sampling procedure in which each element of the population has a fixed probabilistic chance of being selected for the sample”
  • Simple Random Sampling“A probability sampling technique in which eachelement in the population has a known and equalprobability of selection. Every element is selectedindependently of every other element and the sample isdrawn by a random procedure from a sampling frame”For e.g. Lottery system
  • Simple Random Sampling A B C D E 1 6 11 16 21 2 7 12 17 22 3 8 13 18 23 4 9 14 19 24 5 10 15 20 25 • Sampling Elements : 3, 7, 9, 16, 24 • There is no element from Group C.
  • Systematic Sampling “ A probability sampling technique in which the sampleis chosen by selecting a random starting point and thenpicking every ith element in succession from samplingframe “
  • Systematic Sampling A B C D E 1 6 11 16 21 2 7 12 17 22 3 8 13 18 23 4 9 14 19 24 5 10 15 20 25 • Sampling Interval : Population size (25)/sample size (5) • Select a random no. between 1 to 5 (for e.g. 2 ) , select every 5th element from 2 • Sampling Elements : 2, 7, 12, 17, 22 • All the elements of each group is selected
  • Stratified Sampling
  • Exercise 2
  • Cluster Sampling
  • Thank you