7: Sampling Theory and Methods

7-2 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Sampling Sampling is the process of selecting a small number of elements from a larger defined target population of elements such that the information gathered from the small group will allow judgments to be made about the larger population.

7-3 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Census

7-4 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Basics of Sampling Theory Population Element Defined target population Sampling unit Sampling frame

7-5 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Sampling Error Sampling error is any type of bias that is attributable to mistakes in either drawing a sample or determining the sample size.

7-6 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Nonsampling Error Nonsampling error is bias that occurs in a research study regardless of whether a sample or census is used, such as bias caused by measurement error, response errors, non-response error or coding errors.

7-7 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Sampling Methods Probability sampling Nonprobability sampling

7-8 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Types of Sampling Methods Probability  Simple random sampling  Systematic random sampling  Stratified random sampling  Cluster sampling Nonprobability  Convenience sampling  Judgment sampling  Quota sampling  Snowball sampling

7-9 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Simple Random Sampling Simple random sampling is a method of probability sampling in which every unit has an equal nonzero chance of being selected.

7-10 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Systematic Random Sampling Systematic random sampling is a method of probability sampling in which the defined target population is ordered and the sample is selected according to position using a skip interval.

7-11 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Steps in Drawing a Systematic Random Sample  1: Obtain a list of units that contains an acceptable frame of the target population  2: Determine the number of units in the list and the desired sample size  3: Compute the skip interval: SI = [# sampling units available/desired sample size]  4: Determine a random start point  5: Beginning at the start point, select the units by choosing each unit that corresponds to the skip interval

7-12 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Stratified Random Sampling Stratified random sampling is a method of probability sampling in which the population is divided into different subgroups and samples are selected from each.

7-13 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Steps in Drawing a Stratified Random Sample  1: Divide the target population into homogeneous subgroups or strata  2: Draw random samples from each stratum  3: Combine the samples from each stratum into a single sample of the target population

7-14 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Cluster Sampling Cluster sampling is a method of probability sampling where the sampling units are selected in groups rather than individually. The chosen groups are sampled in their entirety.

7-15 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Nonprobability Sampling Methods Convenience sampling relies upon convenience and access Judgment sampling relies upon belief that participants fit characteristics Quota sampling emphasizes representation of specific characteristics Snowball sampling relies upon respondent referrals of others with like characteristics

7-16 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Factors to Consider in Sample Design Research objectivesDegree of accuracy ResourcesTime frame Knowledge of target population Research scope Statistical analysis needs

7-17 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008 Factors Affecting Sample Size for Probability Designs  Variability of the population characteristic under investigation  Level of confidence desired in the estimate  Degree of precision desired in estimating the population characteristic

7-18 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin2008  When estimating a population mean n = (Z 2 B,CL )(σ 2 /e 2 )  When estimating a population proportion n = (Z 2 B,CL )([P x Q]/e 2 ) Probability Sampling and Sample Sizes

7-19 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials of Marketing Research 1e © McGraw-Hill/Irwin Define the Target Population 2. Select the Data Collection Method 3. Identify the Sampling Frame(s) Needed 4. Identify the Appropriate Sampling Method 5. Determine Sample Sizes and Contact Rates 6. Create Plan for Selecting Sampling Units 7. Execute the Operational Plan Steps in Developing a Sampling Plan