Marketing Research Test #2

Front 1

Sections of a Questionnaire

Back 1

1. Interviewer Introduction and Purpose
2. Request for Cooperation
3. Instructions
4. Screening Questions
5. Questions
6. Demographic Questions

Front 2

Guidelines for Questionnaire Design

Back 2

1. No unnecessary questions
2. Consider ability and willingness to respond
3. Use simple words
4. No ambiguous words
5. No biasing, leading questions
6. Don't impose implicit alternatives
7. Don't assume respondent is knowledgable
8. Don't put math on the respondent
9. No double-barrelled questions
10. Sequence of questions should be logical
11. Start with simple questions, have difficult ones later
12. Keep demographic questions at the end
13. Use special methods for personal/embarrassing questions
14. Make questionnaire appealing to the eye
15. Do data analysis with dummy data
16. PRETEST

Front 3

Types of Questions

Back 3

1. Open ended
2. Close ended

Front 4

Reasons to Use Open-Ended Questions

Back 4

1. Intro to a survey or topic
2. When it's important to measure the salience of an issue
3. Too many responses listed
4. Verbatim responses desired
5. Behaviour to be measured is sensitive or disapproved

Front 5

Advantages of Open-Ended Questions

Back 5

1. Wide range of responses
2. Responses obtained without influence
3. Free choices

Front 6

Disadvantages of Open-Ended Questions

Back 6

1. Variability of clarity and responses
2. Time consuming
3. Subjective judgements, summarization prone to error
4. Answers expand or contract according to space/time available
5. Respondents may not use same frame of reference when options aren't available

Front 7

Formats for Close-Ended Questions

Back 7

1. choice from a list of responses
2. appropriate single choice rating on a scale

Front 8

Advantages of Close-Ended Questions

Back 8

1. Easier to answer
2. Require less effort by interviewer
3. Easier tabulation/analysis
4. Less potential error in asking/recording
5. Directly comparable between respondents

Front 9

Limitations of Close-Ended Questions

Back 9

1. Disagreement on type of responses listed
2. Answer received no matter how irrelevant question is
3. May not produce meaningful results
4. Dichotomous questions prone to measurement error because it is polarized
5. Fewer options of self expression
6. Alternative responses provide answers not considered by respondent, leading

Front 10

Approaches to asking sensitive questions

Back 10

1. Casual approach
2. numbered card
3. everybody approach
4. sealed ballot technique
5. Kinsey approach
6. Randomized response technique

Front 11

Reasons for Pretesting Specific Questions

Back 11

1. Variation
2. Meaning
3. Task Difficulty
4. Respondent's interest/attention

Front 12

Reasons to Pretest Questionnaire

Back 12

1. Test flow for clarity/logic
2. Ensure skip patterns are clear
3. Time each section so not too long
4. Capture and maintain interest/attention

Front 13

Considerations for International Research

Back 13

1. Open-ended questions to avoid cultural bias
2. Indirect form for sensitive questions
3. Nonverbal stimuli when illiteracy is high
4.Re-word questions
5. Most problems relate to attitudes, psychographic and lifestyle data

Front 14

Questionnaire Design Process

Back 14

1. Determine survey objectives, resources and constraints
2. Determine data collection method
3. Determine question response format
4. Decide on wording
5. Establish flow and layout
6. Evaluate questionnaire
7. Obtain approval from all relevant parties
8. Pretest and revise
9. Prepare final copy
10. Implement

Front 15

Developing a Sampling Plan

Back 15

1. Define population
2. Choose data collection method
3. Identify sampling frame
4. Select sampling method
5. Determine sample size
6. Develop operation procedures for selecting sampling elements
7. Evaluate operational sampling plan

Front 16

When is census appropriate?

Back 16

1. Small population size
2. Info needed form every individual
3. Cost of making incorrect decision is high
4. sampling errors high

Front 17

When is a sample appropriate?

Back 17

1. Large population size
2. Cost/time to get info is high
3. Quick decision needed
4. INcrease response quality- more individual time
5. Population is homogenous
6. Census impossible

Front 18

Types of Non-Probability Samples

Back 18

1. Convenience
2. Judgemental
3. Quota
4. Snowball

Front 19

Types of Probability Samples

Back 19

1. Simple Random Sample
2. Systematic
3. Stratified
4. Cluster

Front 20

Types of Stratified Sampling

Back 20

1. Proportionate
2. Disproportionate

Front 21

Elements of Stratified Sampling

Back 21

1. Homogeneity within group
2. Heterogeneity between groups
3. All groups included
4. Sampling efficiency improved by increasing accuracy at faster rate than cost

Front 22

Elements of Cluster Sampling

Back 22

1. Homogeneity between groups
2. Heterogeneity within groups
3. Random selection of groups
4. Sampling efficiency improved by decreasing costs faster rate than accuracy

Front 23

When to Use Non-Probability Sampling

Back 23

1. Exploratory stages
2. Pre-testing
3. Homogenous population
4. Lacks statistical knowledge
5. Operational ease required

Front 24

When to Use Ad Hoc Methods of Sample Size

Back 24

1. Know from experience
2. Budgetary Constraints

Front 25

Rules of Thumb for Determining Sample Size

Back 25

1. Each group minimum sample of 100
2. 20-50 fro each sub group
3. Use disproportionate sampling if one group of population is relatively small

Front 26

Factors Determining Sample Size

Back 26

1. number of groups and subgroups within sample
2. value of info
3. accuracy rate
4. cost of sample
5. variability of population

Front 27

Population/Sample Characteristics

Back 27

1. mean
2. variance/standard deviation

Front 28

Determining Statistical Precision

Back 28

1. Sample reliability
2. Standard error
3. interval estimation