Lecture Marketing research - Chapter 10: Basic sampling issues

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After studying this chapter you will be able to: Understand the concept of sampling, learn the steps in developing a sampling plan, understand the concepts of sampling error and nonsampling error, understand the differences between probability samples, and nonprobability samples, understand sampling implications of surveying over the Internet.

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Nội dung Text: Lecture Marketing research - Chapter 10: Basic sampling issues

Learning Objectives CHAPTER Ten Basic Sampling Issues Copyright © 2004 John Wiley & Sons, Inc.
Learning Objectives Learning Objectives 1. To understand the concept of sampling. 2. To learn the steps in developing a sampling plan. 3. To understand the concepts of sampling error and nonsampling error. 4. To understand the differences between probability samples, and nonprobability samples. 5. To understand sampling implications of surveying over the Internet.
Learning Objectives The Concept of Sampling To understand the concept of sampling. Sampling Defined: 1. The process of obtaining information from a subset of a larger group. 2. A market researcher takes the results from the sample to make estimates of the larger group. 3. Sampling a small percentage of a population can result in very accurate estimates.
Learning Objectives Definition Of Important To understand the Terms concept of sampling. Population or Universe 1. The population or population of interest is the total group of people from whom information is needed. 2. Defining the population of interest is the first step in the sampling process 3. Requires good logic and judgment 4. Based on the characteristics of current or target customer Sample versus Census Census: Data about every member of the population. Sample: A subset of the population
Figure 10.1 Learning Steps in Developing Objectives a Sample Plan Step 7. Step 2. Choose Execute Data Collection Operational Plan Method Step1. Define the Population of Step 6. Develop Interest Step 3. Operational Plan Choose Sampling Frame Step 5. (4) Determine Select a Sample Size Sampling Method
Learning Objectives Steps In Developing A To learn the steps in Sampling Plan developing a sample plan. Step One: Defining the Population of Interest Specifying the characteristics from whom information is needed. Define the characteristics of those that should be excluded. Step Two: Choose Data Collection Method Impacts for the sampling process. Step Three: Choosing Sampling Frame A list of elements or members from which we select units to be sampled.
Learning Objectives Steps In Developing A To learn the steps in Sampling Plan developing a sample plan. Step Four: Select a Sampling Method The selection will depend on: • The objectives of the study • The financial resources available • Time limitations • The nature of the problem Probability Samples A known, nonzero probability of selection
Learning Objectives Steps In Developing A To understand the steps in Sampling Plan developing a sample plan. Nonprobability Samples Elements selected in a nonrandom manner. 1. Nonrandomness—selected on the basis of convenience 2. Purposeful nonrandomness—systematically excludes or overrepresents certain subsets of the population
Learning Objectives Steps In Developing A To understand the steps in Sampling Plan developing a sample plan. Advantages Of Probability Samples 1. Information from a representative cross-section 2. Sampling error can be computed 3. Results are projectable to the total population. Disadvantages Of Probability Samples 1. More expansive than nonprobabiity samples 2. Take more time to design and execute.
Learning Objectives Steps In Developing A To understand the steps in Sampling Plan developing a sample plan. Disadvantages of Nonprobability Samples 1. Sampling error cannot be computed 2. Representativeness of the sample is not known 3. Results cannot be projected to the population. Advantages of Nonprobability Samples 1. Cost less than probability 2. Can be conducted more quickly 3. Produces samples that are reasonably representative
Figure 10.2 Learning Objectives Classification of Sampling Methods Sampling methods Probability samples Nonprobabilit y samples Systemati Stratified Convenienc Snowball c e Cluster Simple Judgement Quota random
Learning Objectives Steps In Developing A To distinguish between probability Sampling Plan samples and nonprobability samples. Step Five: Determine Sample Size • Discussed more in depth in Chapter 11 • Acceptable Error • Levels of Confidence
Learning Objectives Steps In Developing A To distinguish between probability Sampling Plan samples and nonprobability samples. Step Six: Develop of Operational Procedures for Selecting Sample Elements Specify whether a probability or nonprobability sample is being used Step Seven: Execution the Sampling Plan The final step of the operational sampling plan Include adequate checking of specified procedures.
Learning Objectives Sampling And To understand the concepts of Nonsampling Errors sampling error and nonsampling error. Sampling Error The error that results when the same sample is not perfectly representative of the population. Two types of sampling error: X= +- +- ns s X = sample mean = true population mean s = sampling error ns = nonsampling error
Learning Objectives Sampling And To understand the concepts of Nonsampling Errors sampling error and nonsampling error. Sampling Error The error that results when the same sample is not perfectly representative of the population. • Administrative error: problems in the execution of the sample • Random error: due to chance and cannot be avoided Measurement or Nonsampling Error Includes everything other than sampling error that can cause inaccuracy and bias
Learning Objectives Probability Sampling To understand the differences in Methods probability and nonprobability sampling methods. Simple Random Sampling The purest form of probability sample Sample Size Probability of Selection = Population Size Systematic Sampling Uses a fixed skip interval to draw elements from a numbered population. Population Size Skip Interval = Sample Size
Learning Objectives Probability Sampling To understand the differences in Methods probability and nonprobability sampling methods. Stratified Samples Probability samples that are distinguished by the following steps: 1. The original population is divided into two or more mutually exclusive and exhaustive subsets 2. Simple random samples of elements from the two or more subsets are chosen independently from each other.
Learning Objectives To understand the differences in Probability Sampling probability and nonprobability Methods sampling methods. Three steps: In implementing a properly stratified sample: 1. Identify salient demographic or classification factors correlated with the behavior of interest. 2. Determine what proportions of the population fall into various sub subgroups under each stratum. • proportional allocation • disproportional or optimal allocation 3. Select separate simple random samples from each stratum
Learning Objectives Probability Sampling To understand the differences in Methods probability and nonprobability sampling methods. Cluster Samples Sampling units are selected in groups. 1. The population of interest is divided into mutually exclusive and exhaustive subsets. 2. A random sample of the subsets is selected. • One-stage cluster—all elements in subset selected • Two-stage cluster—elements selected in some probabilistic manner from the selected subsets
Learning Objectives Nonprobability Sampling To understand the differences in Methods probability and nonprobability sampling methods. Convenience Samples Easy to collect Judgement Samples Based on judgmental selection criteria Quota Samples Demographic characteristics in the same proportion as in the population Snowball Samples Additional respondents selected on referral from initial respondents.