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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Developing the Sampling Plan Chapter 9, Student Edition MR/Brown & Suter 1

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objectives MR/Brown & Suter2 1. Explain the difference between a parameter and a statistic 2. Explain the difference between a probability sample and a nonprobability sample 3. List the primary types of nonprobability samples 4. List the primary types of probability samples 5. Discuss the concept of total sampling elements (TSE) 6. Cite three factors that influence the necessary sample size 7. Explain the relationship between population size and sample size

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objectives MR/Brown & Suter3 1. Explain the difference between a parameter and a statistic 2. Explain the difference between a probability sample and a nonprobability sample 3. List the primary types of nonprobability samples 4. List the primary types of probability samples 5. Discuss the concept of total sampling elements (TSE) 6. Cite three factors that influence the necessary sample size 7. Explain the relationship between population size and sample size

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objective 1 MR/Brown & Suter4 Parameter A characteristic or measure of a population If it were possible to take measures from all members of a population without error, a true value of a parameter could be determined Statistic A characteristic or measure of a sample Statistics are calculated from sample data and used to estimate population parameters

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objectives MR/Brown & Suter5 1. Explain the difference between a parameter and a statistic 2. Explain the difference between a probability sample and a nonprobability sample 3. List the primary types of nonprobability samples 4. List the primary types of probability samples 5. Discuss the concept of total sampling elements (TSE) 6. Cite three factors that influence the necessary sample size 7. Explain the relationship between population size and sample size

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objective 2 MR/Brown & Suter6 Nonprobability Sample A sample that relies on personal judgment in the element selection process Neither sampling error nor the margin of sampling error can be estimated or calculated Techniques include Convenience Judgment Snowball Quota Probability Sample A sample in which each target population element has a known, nonzero chance of being included in the sample Techniques include Simple Random Systematic Stratified Cluster Area

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objective 2 MR/Brown & Suter7 Nonprobability Sample Neither sampling error nor the margin of sampling error can be estimated or calculated Inferences cannot be made about the population Inferences are limited to the sample Thus, results are not generalizable from the sample to the population Probability Sample One can statistically assess level of sampling error Inferences can be made about the population, and not just the sample Inferences are not limited to the sample Thus, results are generalizable from the sample to the population

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objectives MR/Brown & Suter8 1. Explain the difference between a parameter and a statistic 2. Explain the difference between a probability sample and a nonprobability sample 3. List the primary types of nonprobability samples 4. List the primary types of probability samples 5. Discuss the concept of total sampling elements (TSE) 6. Cite three factors that influence the necessary sample size 7. Explain the relationship between population size and sample size

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objective 3 MR/Brown & Suter9 Convenience Sample (Nonprobability Technique) Population elements are sampled simply because they are in the right place at the right time Also called “Accidental” Sample Example – Television news “question of the day” polls

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objective 3 MR/Brown & Suter10 Judgment Sample (Nonprobability Technique) Population elements are handpicked because they are expected to serve the research purpose Example – Hire panelists who are knowledgeable about the issue being researched rather than selecting them at random Snowball Sample (Nonprobability Technique) Initial sample chosen by a probability technique (e.g., systematic sampling) then the population elements are asked for referrals of others they know who might be interested in participation Example – A demand study for a new product where initial respondents know people with a high interest level within the product category

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objective 3 MR/Brown & Suter11 Quota Sample (Nonprobability Technique) Sample chosen so that the proportion of sample elements with certain characteristics is about the same as the proportion of the elements with the characteristics in the target population Stated more simply, certain important characteristics of the population are represented proportionately in the sample Example – Research Problem: Investigate 100 undergraduate student attitudes toward a controversial new technology fee Known Population Parameters: Class (30% Freshman, 20% Sophomores, 30% Juniors, 20% Seniors) and Gender (50% Female, 50% Male) Approach: 10 students will interview 10 friends each for a total of 100 responses

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objectives MR/Brown & Suter12 1. Explain the difference between a parameter and a statistic 2. Explain the difference between a probability sample and a nonprobability sample 3. List the primary types of nonprobability samples 4. List the primary types of probability samples 5. Discuss the concept of total sampling elements (TSE) 6. Cite three factors that influence the necessary sample size 7. Explain the relationship between population size and sample size

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objective 4 MR/Brown & Suter13 Simple Random Sample (Probability Technique) Walking down the street and passing out surveys to unknown people “at random” is “random” in the everyday sense, but not random in a scientific sample sense Example – Sample is drawn by a computer or from a physical list using a random number table

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objective 4 MR/Brown & Suter14 Systematic Sample (Probability Technique) Sample in which every kth element (k = sampling interval) in the population is selected for the sample pool after a random start Example – Research Problem: Investigate 250 undergraduate student attitudes toward controversial new technology fee Known Population: 5000 students published in the campus directory Approach: k = 5000/250 = 20 or 1 out of every 20 students on campus will be surveyed. Randomly select the first name then count down 20 names. Select that person to be surveyed and then count down 20 names again. Select that person and so on until you get 250 names.

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objective 4 MR/Brown & Suter15 Stratified Sample (Probability Technique) Sample in which (1) the population is divided into mutually exclusive and exhaustive subsets and (2) a simple random sample of elements is chosen independently from each group/subset Most appropriate when subsets (or strata) are homogeneous within but heterogeneous between with respect to key variables Example – Phoenix is one subset, Tucson is a second subset, and all other residents within the state of Arizona constitute a third subset

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objective 4 MR/Brown & Suter16 Cluster Sample (Probability Technique) Like stratified sampling, (1) the population is divided into mutually exclusive and exhaustive subsets Unlike stratified sampling, (2) a simple random sample of subsets (i.e., clusters) is chosen Most appropriate when subsets (or strata) are heterogeneous within but homogeneous between with respect to key variables Area Sampling (Probability Technique) A form of cluster sampling that uses census tracks or city blocks as sampling units

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objectives MR/Brown & Suter17 1. Explain the difference between a parameter and a statistic 2. Explain the difference between a probability sample and a nonprobability sample 3. List the primary types of nonprobability samples 4. List the primary types of probability samples 5. Discuss the concept of total sampling elements (TSE) 6. Cite three factors that influence the necessary sample size 7. Explain the relationship between population size and sample size

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objective 5 MR/Brown & Suter18 It is common that information cannot be collected from or about all elements chosen for a sample Bad contact information Refusal to participate Inability to reach the potential respondent To overcome this inevitable situation, it is usually necessary to draw a larger number of sample elements to ultimately achieve the desired sample size This larger number of elements is known as total sampling elements (TSE)

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objectives MR/Brown & Suter19 1. Explain the difference between a parameter and a statistic 2. Explain the difference between a probability sample and a nonprobability sample 3. List the primary types of nonprobability samples 4. List the primary types of probability samples 5. Discuss the concept of total sampling elements (TSE) 6. Cite three factors that influence the necessary sample size 7. Explain the relationship between population size and sample size

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objective 6 MR/Brown & Suter20 Three basic factors affect the size of sample needed when working with a probability sample Amount of Diversity or Variation As diversity/variation increases, larger samples are required Degree of Precision As need for precision increases, larger samples are required Degree of Confidence Confidence increases as sample size increases At any given sample size, there is a trade-off between confidence and precision. Higher precision means lower confidence unless we can increase the sample size

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objectives MR/Brown & Suter21 1. Explain the difference between a parameter and a statistic 2. Explain the difference between a probability sample and a nonprobability sample 3. List the primary types of nonprobability samples 4. List the primary types of probability samples 5. Discuss the concept of total sampling elements (TSE) 6. Cite three factors that influence the necessary sample size 7. Explain the relationship between population size and sample size

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© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Learning Objective 7 MR/Brown & Suter22 Size of the population has no bearing on the size of the sample Desired variation, precision, and confidence drive the sample size Variation is outside the researcher’s control; it’s an artifact of the population Precision and Confidence are inversely related The more similar the population elements, the few people needed regardless of how large the population is

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