4 research design + sampling methods dr. hueihsia holloman
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The document describes various research methods being used by different companies and organizations. Some key points: - A food manufacturer is conducting research to understand the demographics of organic food purchasers. - British Airways is testing in-flight internet services on one of its flights from New York to Tokyo, charging different prices ($30 one week, $15 the next) to test consumer response. - Cosmopolitan magazine is sending different magazine covers (one with a female model, one with female and male models) to different reader groups to test differences in purchase response.
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4 research design + sampling methods dr. hueihsia holloman
- 1. Wk 4 Data Collection Dr. Huei Holloman
- 4. The goal of this research is to discover the real nature of the problem & to suggest new possible solutions or new ideas. A food manufacturer wants to know the demographics of people who purchase organic foods. A firm is considering hiring American celebrity Paris Hilton to endorse its products. British Airways would like to test in-flight Internet services on one of its regular flights from New York to Tokyo. The company charges $30 one week and $15 the next week. This type of study attempts to discover answers to the following questions: who, what, when, where, or how much. A manufacturer investigates whether consumers will buy a new pill that replaces eating a meal. Cosmopolitan magazine sends out a cover in selected markets featuring a female model to half of its readers and a cover with a female and male model to the other half of its readers to test differences in purchase response between the two groups. A hair-care manufacturer interviews wholesalers, retailers, and customers to determine the potential for a new shampoo package. This type of research attempts to capture a population’s characteristics by making inference from a sample’s characteristics and testing hypotheses. Descriptive On the CBS television show Undercover Boss, top executives disguised as middle level or lower
- 6. Chapter 11 Measurement McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
- 7. 11-7 Learning Objectives Understand . . . • The distinction between measuring objects, properties, and indicants of properties. • The similarities and differences between the four scale types used in measurement and when each is used. • The four major sources of measurement error. • The criteria for evaluating good measurement.
- 8. 11-8 Measurements Will Vary Over Time “The only man who behaved sensibly was my tailor; he took my measurement anew every time he saw me, while all the rest went on with their old measurements and expected them to fit me.” George Bernard Shaw playwright and essayist
- 9. 11-9 PulsePoint: Research Revelation 32.5 The percent of corporations using or planning to use cloud computing—using software and server space via Internet sources.
- 10. Measurement in research consists of: • assigning numbers to empirical events, objects or properties, or activities in compliance w/ a set of rules. • Textbook uses an example of auto show attendance. • A mapping rule is a scheme for assigning numbers to aspects of an empirical event.
- 13. Levels of Measurement Ordinal interval Ratio Nominal Classification Order ( > or < ) Classification • Order means that the numbers are ordered. One number is greater than, less than, or equal to another number. E.g., Pizza Hut is better than Papa Johns, ranking
- 15. 11-15 Ordinal Scales • Ordinal data require conformity to a logical postulate, which states: If a is greater than b, and b is greater than c, then a is greater than c. • The appropriate measure of central tendency is the median. The median is the midpoint of a distribution. A percentile or quartile reveals the dispersion.
- 16. 11-16 Levels of Measurement Ordinal interval Ratio Nominal Classification Order Classification Order Classification Distance
- 17. 11-17 Levels of Measurement Ordinal interval Ratio Nominal Classification Order Classification Order Classification Distance Natural Origin Order Classification Distance
- 18. Ratio Scales 11-18 Examples Weight Height Number of children • Ratio data : actual amounts of a variable. • E.g., monetary values, population counts, distances, return rates, and amounts of time. • Central tendency and coefficients of variation may also be calculated. • Higher levels of measurement generally yield more information and are appropriate for more powerful statistical procedures.
- 19. 11-19 Sources of Error 1. Respondents may also suffer from temporary factors like fatigue and boredom. 2. Any condition that places a strain on the interview 3. The interviewer can distort responses by rewording, paraphrasing, or reordering questions. • Stereotypes in appearance and action also introduce bias. • Careless mechanical processing will distort findings and can also introduce problems in the data analysis stage through incorrect coding, careless tabulation, and faulty statistical calculation. 4. A defective instrument • confusing and ambiguous. • not explore all the potentially important issues.
- 20. 11-20 Evaluating Measurement Tools Criteria Validity Practicality Reliability • Validity is the extent to which a test measures what we actually wish to measure. • Reliability refers to the accuracy and precision of a measurement procedure. • Practicality is concerned with a wide range of factors of economy, convenience, and interpretability.
- 21. 11-21 Understanding Validity and Reliability
- 26. 11-26 Increasing Construct Validity New measure of trust Known measure of trust Empathy Credibility
- 28. 11-28 Judging Criterion Validity Relevance Freedom from bias Reliability Availability Criterion
- 31. 11-31 Key Terms • Internal validity • Interval scale • Mapping rules • Measurement • Nominal scale • Objects • Ordinal scale • Practicality • Properties • Ratio scale • Reliability – Equivalence – Internal consistency – Stability • Validity – Construct – Contents – Criterion-related
- 32. Chapter 12 Measurement Scales McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
- 33. 12-33 Learning Objectives Understand… • The nature of attitudes and their relationship to behavior. • The critical decisions involved in selecting an appropriate measurement scale. • The characteristics and use of rating, ranking, sorting, and other preference scales.
- 34. 12-34 Measurements are Relative “Any measurement must take into account the position of the observer. There is no such thing as measurement absolute, there is only measurement relative.” Jeanette Winterson journalist and author
- 35. 12-35 PulsePoint: Research Revelation 34 The percent of workers who are considered truly loyal.
- 37. 12-37 Nature of Attitudes Cognitive I think oatmeal is healthier than corn flakes for breakfast. Affective Behavioral I hate corn flakes. I intend to eat more oatmeal for breakfast. “All survey questions must be actionable if you want results.” Frank Schmidt, senior scientist The Gallup Organization
- 38. Response biases & sampling
- 39. Improving Predictability of Attitudes Reference groups Multiple measures Factors Strong Specific Basis Direct Factors the applicability of attitudinal research for business. 1. Specific attitudes are better predictors of behavior 2. Strong attitudes are better predictors of behavior composed of little intensity or topic interest. 3. Direct experiences with the attitude object produce behavior more reliably. 4. Cognitive-based attitudes influence behaviors better than affective-based attitudes.
- 40. 12-40 Measurement Scales “All survey questions must be actionable if you want results.” Frank Schmidt, senior scientist The Gallup Organization
- 41. Selecting a Measurement Scale Research objectives Response types Data properties Number of dimensions Forced or unforced choices Balanced or unbalanced Rater errors Number of scale points Attitude scaling: process of assessing an attitudinal disposition using a number that represents a person’s score on an attitudinal continuum ranging from an extremely favorable disposition to an extremely unfavorable one.
- 42. 12-42 Response Types Rating scale Ranking scale Categorization Sorting
- 43. 12-43 Dimensions -Religion, depression symptoms, democracy Unidimensional Multi-dimensional
- 44. 12-44 Balanced or Unbalanced Very bad Bad Neither good nor bad Good Very good Poor Fair Good Very good Excellent How good an actress is Angelina Jolie?
- 45. 12-45 Forced or Unforced Choices Very bad Bad Neither good nor bad Good Very good Very bad Bad Neither good nor bad Good Very good No opinion Don’t know How good an actress is Angelina Jolie?
- 46. Number of Scale Points Very bad Bad Neither good nor bad Good Very good Very bad Somewhat bad A little bad Neither good nor bad A little good Somewhat good Very good How good an actress is Angelina Jolie?
- 47. Rater Errors Error of central tendency Error of leniency •Adjust strength of descriptive adjectives •Space intermediate descriptive phrases farther apart •Provide smaller differences in meaning between terms near the ends of the scale •Use more scale points
- 48. 12-48 Rater Errors Primacy Effect Recency Effect Reverse order of alternatives periodically or randomly
- 49. Rater Errors Halo Effect • Rate one trait at a time • Reveal one trait per page • Reverse anchors periodically • The halo effect is the systematic bias that the rater introduces by carrying over a generalized impression of the subject from one rating to another. e.g., a teacher may expect that a student who did well on the first exam to do well on the second.
- 50. 12-50 Simple Category Scale I plan to purchase a MindWriter laptop in the 12 months. Yes No
- 51. 12-51 Multiple-Choice, Single-Response Scale What newspaper do you read most often for financial news? East City Gazette West City Tribune Regional newspaper National newspaper Other (specify:_____________)
- 52. 12-52 Multiple-Choice, Multiple-Response Scale What sources did you use when designing your new home? Please check all that apply. Online planning services Magazines Independent contractor/builder Designer Architect Other (specify:_____________)
- 53. 12-53 Likert Scale The Internet is superior to traditional libraries for comprehensive searches. Strongly disagree Disagree Neither agree nor disagree Agree Strongly agree
- 54. Semantic Differential • studies of brand and institutional image, employee morale, safety, financial soundness, trust, etc. • usually with 7 points, by which one or more participants rate one or more concepts on each scale item. • Proposition: an object can have several dimensional meaning located in multidimensional property space, called semantic space.
- 55. Adapting SD Scales Convenience of Reaching the Store from Your Location Nearby ___: ___: ___: ___: ___: ___: ___: Distant Short time required to reach store ___: ___: ___: ___: ___: ___: ___: Long time required to reach store Difficult drive ___: ___: ___: ___: ___: ___: ___: Easy Drive Difficult to find parking place ___: ___: ___: ___: ___: ___: ___: Easy to find parking place Convenient to other stores I shop ___: ___: ___: ___: ___: ___: ___: Inconvenient to other stores I shop Products offered Wide selection of different kinds of products ___: ___: ___: ___: ___: ___: ___: Limited selection of different kinds of products Fully stocked ___: ___: ___: ___: ___: ___: ___: Understocked Undependable products ___: ___: ___: ___: ___: ___: ___: Dependable products High quality ___: ___: ___: ___: ___: ___: ___: Low quality Numerous brands ___: ___: ___: ___: ___: ___: ___: Few brands Unknown brands ___: ___: ___: ___: ___: ___: ___: Well-known brands
- 56. 12-56 SD Scale for Analyzing Actor Candidates
- 57. 12-57 Graphic of SD Analysis
- 58. Numerical Scale • Numerical scales have equal intervals that separate their numeric scale points. The verbal anchors serve as the labels for the extreme points. • Numerical scales are often 5-point scales but may have 7 or 10 points. • The participants write a number from the scale next to each item. • It produces either ordinal or interval data.
- 59. Multiple Rating List Scales “Please indicate how important or unimportant each service characteristic is:” IMPORTANT UNIMPORTANT Fast, reliable repair 7 6 5 4 3 2 1 Service at my location 7 6 5 4 3 2 1 Maintenance by manufacturer 7 6 5 4 3 2 1 Knowledgeable technicians 7 6 5 4 3 2 1 Notification of upgrades 7 6 5 4 3 2 1 Service contract after warranty 7 6 5 4 3 2 1 Exhibit 12-3: A multiple rating scale is similar to the numerical scale but differs in 2 ways: 1) it accepts a circled response from the rater, and 2) the layout facilitates visualization of the results. • This scale produces interval data.
- 60. • Used as an alternative to the semantic differential, especially when it is difficult to find bipolar adjectives that match the investigative question. • interval data. Stapel Scales: 3 attributes of corporate image.
- 61. Constant-Sum Scales • The participant allocates points to more than one attribute or property indicant, such that they total a constant sum, usually 100 or 10. • Participant precision and patience suffer when too many stimuli are proportioned and summed. • A participant’s ability to add may also be taxed. • Its advantage is its compatibility with percent and the fact that alternatives that are perceived to be equal can be so scored. • This scale produces interval data.
- 63. 12-63 Ranking Scales (see next slides…) Paired-comparison scale Forced ranking scale Comparative scale
- 65. Forced Ranking Scale • This method is faster than paired comparisons and is usually easier and more motivating to the participant. • A drawback of this scale is the limited number of stimuli (usually no more than 7) that can be handed by the participant. • This scale produces ordinal data.
- 67. Sorting
- 68. 12-68 MindWriter Scaling Likert Scale The problem that prompted service/repair was resolved Strongly Disagree Disagree Neither Agree Nor Disagree Agree Strongly Agree 1 2 3 4 5 Numerical Scale (MindWriter’s Favorite) To what extent are you satisfied that the problem that prompted service/repair was resolved? Very Dissatisfied Very Satisfied 1 2 3 4 5 Hybrid Expectation Scale Resolution of the problem that prompted service/repair. Met Few Expectations Met Some Expectations Met Most Expectations Met All Expectations Exceeded Expectations 1 2 3 4 5
- 69. 12-69 Ideal Scalogram Pattern (social distance, organizational hierarchies, and evolutionary product stages) Item Participant Score 2 4 1 3 X X X X 4 __ X X X 3 __ __ X X 2 __ __ __ X 1 __ __ __ __ 0 * X = agree; __ = disagree.
- 70. Key Terms • Attitude • Balanced rating scale • Categorization • Comparative scale • Constant-sum scale • Cumulative scale • Error of central tendency • Error of leniency • Forced-choice rating scale • Forced ranking scale • Graphic rating scale • Halo effect • Item analysis • Likert scale • Multidimensional scale • Multiple-choice, multiple-response scale • Multiple-choice, single-response scale • Multiple rating list • Numerical scale • Paired-comparison scale • Q-sort • Ranking scale • Rating scale • Scaling • Scalogram analysis • Semantic differential • Simple category scale
- 71. 12-71 Key Terms • Sorting • Stapel scale • Summated rating scale • Unbalanced rating scale • Unforced-choice rating scale • Unidimensional scale
- 72. Chapter 13 Questionnaires and Instruments McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
- 73. 13-73 Learning Objectives Understand... • The link forged between the management dilemma and the communication instrument by the management-research question hierarchy. • The influence of the communication method on instrument design. • The three general classes of information and what each contributes to the instrument.
- 74. 13-74 Learning Objectives Understand . . . • The influence of question content, question wording, response strategy, and preliminary analysis planning on question construction. • Each of the numerous question design issues influencing instrument quality, reliability, and validity. • The sources for measurement questions • The importance of pretesting questions and instruments.
- 75. 13-75 Measurement Skepticism “Research that asks consumers what they did and why is incredibly helpful. Research that asks consumers what they are going to do can often be taken with a grain of salt.” Al Ries author, co-founder, and chairman Ries & Ries.
- 76. 13-76 PulsePoint: Research Revelation 60 The percent of businesses hit annually by cybercrime.
- 77. 13-77 Overall Flowchart for Instrument Design
- 78. 13-78 Flowchart for Instrument Design Phase 1
- 79. Strategic Concerns in Instrument Design What type of scale is needed? What communication approach will be used? Should the questions be structured? Should the questioning be disguised?
- 80. 13-80 Technology Affects Questionnaire Development WebSurveyor used to write an instrument. Write questionnaires more quickly Create visually driven instruments Eliminate manual data entry Save time in data analysis
- 81. 13-81 Disguising Study Objectives Situations where disguise is unnecessary Willingly shared, Conscious-level information Reluctantly shared, Conscious-level information Knowable, Limited-conscious- level information Subconscious-level information
- 82. 13-82 Dummy Table for American Eating Habits Age Use of Convenience Foods Always Use Use Frequently Use Sometimes Rarely Use Never Use 18-24 25-34 35-44 55-64 65+
- 83. 13-83 Flowchart for Instrument Design Phase 2
- 84. Question Categories and Structure Administrative Target Classification 3 categories of measurement questions. 1. Administrative questions identify the participant, interviewer, interviewer location, and conditions. These questions are rarely asked of the participant but are necessary for studying patterns within the data and identify possible error sources. 2. Classification questions usually cover sociological-demographic variables that allow participants’ answers to be grouped so that patterns are revealed and can be studied. These questions usually appear at the end of a survey. 3. Target questions address the investigative questions of a specific study. These are grouped by topic in the survey. Target questions may be structured or unstructured.
- 85. 13-85 Engagement = Convenience “Participants are becoming more and more aware of the value of their time. The key to maintaining a quality dialog with them is to make it really convenient for them to engage, whenever and wherever they want.” Tom Anderson managing partner Anderson Analytics
- 86. 13-86 Question Content Should this question be asked? Is the question of proper scope and coverage? Can the participant adequately answer this question as asked? Will the participant willingly answer this question as asked?
- 87. Criteria of Question Wording Criteria Shared vocabulary Single meaning Misleading assumptions Adequate alternatives Personalized Biased 1. Is the question stated in terms of a shared vocabulary? 2. Does the question contain vocabulary with a single meaning? 3. Does the question contain unsupported or misleading assumptions? 4. Does the question contain biased wording? 5. Is the question correctly personalized? 6. Are adequate alternatives presented within the question?
- 88. Response Strategy Factors Objectives of the study Participant’s level of information Degree to which participants have thought through topic Ease and clarity with which participant communicates Participant’s motivation to share In choosing response options in questions, researchers must consider these factors.
- 89. 13-89 Free-Response Strategy - open-ended questions What factors influenced your enrollment in Metro U? ____________________________________________ ____________________________________________
- 90. Dichotomous Response Strategy Did you attend the “A Day at College” program at Metro U? Yes No Which one of the following factors was most influential in your decision to attend Metro U? Good academic standing Specific program of study desired Enjoyable campus life Many friends from home High quality of faculty Multiple Choice Response Strategy
- 91. Checklist Response Strategy Which of the following factors influenced your decision to enroll in Metro U? (Check all that apply.) Tuition cost Specific program of study desired Parents’ preferences Opinion of brother or sister Many friends from home attend High quality of faculty Strongly influential Somewhat Not at all Good academic reputation Enjoyable campus life Many friends High quality faculty Semester calendar
- 92. Ranking Please rank-order your top three factors from the following list based on their influence in encouraging you to apply to Metro U. Use 1 to indicate the most encouraging factor, 2 the next most encouraging factor, etc. _____ Opportunity to play collegiate sports _____ Closeness to home _____ Enjoyable campus life _____ Good academic reputation _____ High quality of faculty
- 93. 13-93 Summary of Scale Types Type Restrictions Scale Items Data Type Rating Scales Simple Category Scale • Needs mutually exclusive choices One or more Nominal Multiple Choice Single-Response Scale • Needs mutually exclusive choices • May use exhaustive list or ‘other’ Many Nominal Multiple Choice Multiple-Response Scale (checklist) • Needs mutually exclusive choices • Needs exhaustive list or ‘other’ Many Nominal Likert Scale • Needs definitive positive or negative statements with which to agree/disagree One or more Ordinal Likert-type Scale •Needs definitive positive or negative statements with which to agree/disagree One or more Ordinal
- 94. 13-94 Summary of Scale Types Type Restrictions Scale Items Data Type Rating Scales Numerical Scale Needs concepts with standardized meanings; Needs number anchors of the scale or end- points Score is a measurement of graphical space One or many Ordinal or Interval Multiple Rating List Scale Needs words that are opposites to anchor the end-points on the verbal scale Up to 10 Ordinal Fixed Sum Scale Participant needs ability to calculate total to some fixed number, often 100. Two or more Interval or Ratio
- 95. Summary of Scale Types Type Restrictions Scale Items Data Type Rating Scales Stapel Scale Needs verbal labels that are operationally defined or standard. One or more Ordinal or Interval Graphic Rating Scale Needs visual images that can be interpreted as positive or negative anchors Score is a measurement of graphical space from one anchor. One or more Ordinal (Interval, or Ratio) Ranking Scales Paired Comparison Scale • Number is controlled by participant’s stamina and interest. Up to 10 Ordinal Forced Ranking Scale • Needs mutually exclusive choices. Up to 10 Ordinal or Interval Comparative Scale • Can use verbal or graphical scale. Up to 10 Ordinal
- 96. Internet Survey Scale Options
- 97. 13-97 Internet Survey Scale Options
- 99. Sources of Questions • Handbook of Marketing Scales • The Gallup Poll Cumulative Index • Measures of Personality and Social-Psychological Attitudes • Measures of Political Attitudes • Index to International Public Opinion • Sourcebook of Harris National Surveys • Marketing Scales Handbook • American Social Attitudes Data Sourcebook
- 101. 13-101 Guidelines for Question Sequencing Interesting topics early Simple topics early Sensitive questions later Classification questions later Transition between topics Reference changes limited
- 102. 13-102 Illustrating the Funnel Approach 1. How do you think this country is getting along in its relations with other countries? 2. How do you think we are doing in our relations with Iran? 3. Do you think we ought to be dealing with Iran differently than we are now? (If yes) What should we be doing differently? 4. Some people say we should get tougher with Iran and others think we are too tough as it is; how do you feel about it?
- 106. 13-106 Overcoming Instrument Problems Build rapport Redesign question process Explore alternatives Use other methods Pretest
- 107. 13-107 Key Terms • Administrative question • Branched question • Buffer question • Checklist • Classification question • Dichotomous question • Disguised question • Double-barreled question • Free-response question • Interview schedule • Leading question • Multiple-choice question • Pretesting • Primacy effect • Ranking question • Rating question • Recency effort • Screen question • Structured response • Target question – Structured – Unstructured • Unstructured response
- 108. Chapter 14 Sampling McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
- 109. 14-109 Small Samples Can Enlighten “The proof of the pudding is in the eating. By a small sample we may judge of the whole piece.” Miguel de Cervantes Saavedra author
- 110. 14-110 PulsePoint: Research Revelation 80 The average number of text messages sent per day by American teens.
- 111. Sampling Methods
- 112. 14-112 The Nature of Sampling •Population •Population Element •Census •Sample •Sampling frame
- 113. 14-113 Why Sample? Greater accuracy Availability of elements Greater speed Sampling provides Lower cost
- 114. 14-114 What Is a Sufficiently Large Sample? “In recent Gallup ‘Poll on polls,’ . . . When asked about the scientific sampling foundation on which polls are based . . . most said that a survey of 1,500 – 2,000 respondents—a larger than average sample size for national polls—cannot represent the views of all Americans.” Frank Newport The Gallup Poll editor in chief The Gallup Organization
- 115. 14-115 When Is a Census Appropriate? NecessaryFeasible
- 116. 14-116 What Is a Valid Sample? Accurate Precise
- 117. 14-117 Sampling Design within the Research Process
- 118. 14-118 Types of Sampling Designs Element Selection Probability Nonprobability Unrestricted Simple random Convenience Restricted Complex random Purposive Systematic Judgment Cluster Quota Stratified Snowball Double
- 119. 14-119 Steps in Sampling Design What is the target population? What are the parameters of interest? What is the sampling frame? What is the appropriate sampling method? What size sample is needed?
- 120. 14-120 When to Use Larger Sample? Desired precision Number of subgroups Confidence level Population variance Small error range
- 121. Simple Random Advantages • Easy to implement with random dialing Disadvantages • Requires list of population elements • Time consuming • Larger sample needed • Produces larger errors • High cost Systematic Advantages • Simple to design • Easier than simple random • Easy to determine sampling distribution of mean or proportion Disadvantages • Periodicity within population may skew sample and results • Trends in list may bias results • Moderate cost
- 122. 14-122 Stratified Advantages • Control of sample size in strata • Increased statistical efficiency • Provides data to represent and analyze subgroups • Enables use of different methods in strata Disadvantages • Increased error if subgroups are selected at different rates • Especially expensive if strata on population must be created • High cost
- 123. 14-123 Cluster Advantages • Provides an unbiased estimate of population parameters if properly done • Economically more efficient than simple random • Lowest cost per sample • Easy to do without list Disadvantages • Often lower statistical efficiency due to subgroups being homogeneous rather than heterogeneous • Moderate cost
- 124. 14-124 Stratified and Cluster Sampling Stratified • Population divided into few subgroups • Homogeneity within subgroups • Heterogeneity between subgroups • Choice of elements from within each subgroup Cluster • Population divided into many subgroups • Heterogeneity within subgroups • Homogeneity between subgroups • Random choice of subgroups
- 125. 14-125 Area Sampling
- 126. 14-126 Double Sampling Advantages • May reduce costs if first stage results in enough data to stratify or cluster the population Disadvantages • Increased costs if discriminately used
- 127. 14-127 Nonprobability Samples Cost Feasibility Time No need to generalize Limited objectives
- 129. 14-129 Key Terms • Area sampling • Census • Cluster sampling • Convenience sampling • Disproportionate stratified sampling • Double sampling • Judgment sampling • Multiphase sampling • Nonprobability sampling • Population • Population element • Population parameters • Population proportion of incidence • Probability sampling • Proportionate stratified sampling • Quota sampling • Sample statistics • Sampling • Sampling error • Sampling frame • Sequential sampling • Simple random sample • Skip interval • Snowball sampling • Stratified random sampling • Systematic sampling • Systematic variance
- 130. Appendix 14a Determining Sample Size McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
- 133. 14-133 Confidence Levels & the Normal Curve
- 134. 14-134 Standard Errors Standard Error (Z score) % of Area Approximate Degree of Confidence 1.00 68.27 68% 1.65 90.10 90% 1.96 95.00 95% 3.00 99.73 99%
- 136. 14-136 Estimates of Dining Visits Confidence Z score % of Area Interval Range (visits per month) 68% 1.00 68.27 9.48-10.52 90% 1.65 90.10 9.14-10.86 95% 1.96 95.00 8.98-11.02 99% 3.00 99.73 8.44-11.56
- 137. 14-137 Calculating Sample Size for Questions involving Means Precision Confidence level Size of interval estimate Population Dispersion Need for FPA
- 138. 14-138 Metro U Sample Size for Means Steps Information Desired confidence level 95% (z = 1.96) Size of the interval estimate .5 meals per month Expected range in population 0 to 30 meals Sample mean 10 Standard deviation 4.1 Need for finite population adjustment No Standard error of the mean .5/1.96 = .255 Sample size (4.1)2/ (.255)2 = 259
- 139. 14-139 Proxies of the Population Dispersion • Previous research on the topic • Pilot test or pretest • Rule-of-thumb calculation – 1/6 of the range
- 140. 14-140 Metro U Sample Size for Proportions Steps Information Desired confidence level 95% (z = 1.96) Size of the interval estimate .10 (10%) Expected range in population 0 to 100% Sample proportion with given attribute 30% Sample dispersion Pq = .30(1-.30) = .21 Finite population adjustment No Standard error of the proportion .10/1.96 = .051 Sample size .21/ (.051)2 = 81
- 141. 14-141 Appendix 14a: Key Terms • Central limit theorem • Confidence interval • Confidence level • Interval estimate • Point estimate • Proportion
- 142. Addendum: Keynote CloseUp McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
- 145. Determining Sample Size Appendix 14a McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
- 148. 14-148 Metro U. Dining Club Study