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A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

A

ANALYSIS OF VARIANCE
14. Analysis of Variance: One-factor Designs
18. Analysis of Ratios of Means
24. Interpretation of t-Test Results

ARCSIN TRANSFORMATION
ATTRIBUTABLE EFFECT
50. Statistical Analyses of Extreme Proportions
57. Estimation of the Effect of Attributes on Overall Liking

B

BAYESIAN INFERENCE
55. Use of a Bayesian Orientation in Product Testing

BIAS
-Influence Of Brand Name In Product Test
16. Using Letters to Identify Products or Brands
-Product Order Presentation
16. Using Letters to Identify Products or Brands
-Question Order Presentation
1. An Examination of Order Bias (On self-administered questionnaires)
9. Pricing Research: Single vs. Multiple Presentations
15. Do You Want Overall Opinions or Diagnostic Information
-Respondent Fatigue
12. Measuring Buying Intention: Product List vs. Single Product Questionnaire
-Response Bias
4. Number-type Data: Structured vs. Open-ends
-Sampling
36. The Logic of Statistical Significance Tests

BINARY DATA
-Compared to rating scales
53. The Effect of the Number of Scale Points in Measuring Product Perceptions
-Measures of Relationship
40. Measures of Relationship for Binary Data

BINOMIAL DISTRIBUTION
11. Market Share Estimates and Their Standard Errors from Store Tests
32. Estimating Sample Sizes for Mailouts
50. Statistical Analyses of Extreme Proportions

BONFERRONI INEQUALITY
20. Examining Group Differences: Components of t- Plots
30. Testing Differences Among Several Means
38. Correctly Selecting the Best Product

BOOTSTRAPPING
31. Bootstrapping
38. Correctly Selecting the Best Product
48. An Alternative to the Mean

BOX AND WHISKER PLOTS
17. Graphic Displays of Data: Box and Whisker Plots

BRAND SHARE, ESTIMATION OF
11. Market Share Estimates and Their Standard Errors from Store Tests
31. Bootstrapping

C

CASH INCENTIVE
-Mail Survey Response
39. Using a Cash Incentive to Heighten Mail Survey Response

CARRY-OVER EFFECT
13. Repeat Measures Design and Analysis

CENSORED SCALES
4. Number-type Data: Structured vs. Open-ends
52. Censored Scales

CENTRAL TENDENCY
17. Graphic Displays of Data: Box and Whisker Plots
48. An Alternative to the Mean

CENTRAL LOCATION TESTING
51. Factors Involved in Conducting Product Tests via Central Location Facilities

CHOICE, ANALYSIS OF
26. Analysis of Forced-Choice Data

CLUSTER ANALYSIS
25. Function Plots of Multi-Dimensional Data
29. Displaying Group Differences Using Biplots
35. An Analysis of Multiple Brand Usage
60. An Analysis of Importance Ratings

CLUSTERING CONCEPTS
42. Clustering Concepts

COMPONENT OF t-PLOT
20. Examining Group Differences: Components of t- Plots

CONCEPT TESTING
46 -Color vs. Black & White Product Photographs

CONCERN SCALES vs. IMPORTANCE RATINGS
44. The Use of Concern Scales as an Alternative to Importance Ratings

CONDITIONAL PROBABILITY
35. An Analysis of Multiple Brand Usage
57. Estimation of the Effect of Attributes on Overall Liking

CONFIDENCE INTERVAL
11. Market Share Estimates and Their Standard Errors from Store Tests
18. Analysis of Ratios of Means
20. Examining Group Differences: Components of t- Plots
30. Testing Differences Among Several Means
31. Bootstrapping
34. Confidence and Tolerance Intervals
36. The Logic of Statistical Significance Tests

CONFIDENCE LEVEL (See Type I error, significance level)
27. Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels
30. Testing Differences Among Several Means
36. The Logic of Statistical Significance Tests
37. Sample Sizes for Analyses of Means and Proportions
43. Balancing Confidence and Power for Decision Making

CONJOINT ANALYSIS
19. Response Measures, Data Collection Methods, and Conjoint Analysis: A Two-attribute Case Study
58. Conjoint Analysis for Product Strategy Decisions

CONTEXT EFFECTS
6. Brand Perceptions: Relative vs. Absolute Ratings
9. Pricing Research: Single vs. Multiple Presentations
13. Repeat Measures Design and Analysis
41. Some Methodological Issues in Product Testing

CORRECT SELECTION METHODOLOGY
38. Correctly Selecting the Best Product

CORRELATION POINT-BISERIAL
24. Interpretation of t-Test Results

D

DATA COLLECTION METHODS
1. An Examination of Order Bias (On self-administered questionnaires)
8. Using Multiple Question Grids
51. Factors Involved in Conducting Product Tests via Central Location Facilities

DESIGNS
-Partially Balanced Incomplete Block
41. Some Methodological Issues in Product Testing
49. Statistical Designs for Ordering and Rotating Products in Product Tests

-Balanced Incomplete Block Design
49. Statistical Designs for Ordering and Rotating Products in Product Tests

-Incomplete Block
13. Repeat Measures Design and Analysis
29. Displaying Group Differences Using Biplots
41. Some Methodological Issues in Product Testing

-Monadic, Randomized Block, & Repeated Measures
13. Repeat Measures Design and Analysis

DIAGNOSTIC INFORMATION
15. Do You Want Overall Opinions or Diagnostic Information

DISCRIMINANT ANALYSIS
25. Function Plots of Multi-Dimensional Data
29. Displaying Group Differences Using Biplots

DISCRIMINATION
-Tests, Design of & Measurement of
33. Simultaneous Measurement of Discrimination and Preference

DISCRIMINATOR/NON-DISCRIMINATOR MODEL, DOUBLE PAIR PROCEDURE, & DUAL TRIAD PROCEDURE
33. Simultaneous Measurement of Discrimination and Preference

E

EFFECT SIZE
36. The Logic of Statistical Significance Tests

F

FORCED-CHOICE DATA
26. Analysis of Forced-Choice Data
38. Correctly Selecting the Best Product

FREQUENCY
-Distribution
17. Graphic Displays of Data: Box and Whisker Plots

-Frequency Of Use
--"average period" method of measurement
--"past period" method of measurement
--measurement of
7. Frequency Measurement: Past vs. Average Period

FUNCTION PLOT
25. Function Plots of Multi-Dimensional Data

G

GRAPHIC DISPLAY OF DATA
17. Graphic Displays of Data: Box and Whisker Plots
20. Examining Group Differences: Components of t- Plots
25. Function Plots of Multi-Dimensional Data
29. Displaying Group Differences Using Biplots
53. The Effect of the Number of Scale Points in Measuring Product Perceptions
56. Triangle Plots: Graphic Display of "Just Right" Scale Data

H

HYPOTHESIS TESTING
36. The Logic of Statistical Significance Tests
54. Test of Differences Between Correlated Proportions

I

IMPORTANCE, MEASUREMENT OF
28. Measuring the "Importance" of Attributes

IMPORTANCE SCALES
44. The Use of Concern Scales as an Alternative to Importance Ratings

INTERQUARTILE RANGE
17. Graphic Displays of Data: Box and Whisker Plots

AN ANALYSIS OF IMPORTANCE RATINGS
60. An Analysis of Importance Ratings

J

JACKKNIFING
11. Market Share Estimates and Their Standard Errors from Store Tests
31. Bootstrapping

"JUST RIGHT" SCALES
56. Triangle Plots: Graphic Display of "Just Right" Scale Data

L

LETTER BIAS IN PRODUCT LABELING
16. Using Letters to Identify Products or Brands

LISTED VS. UNLISTED TELEPHONE NUMBERS
10. Dialing Selection Techniques: Random Digit vs. Directory

M

MAIL PANELS
59. Mail Panels vs. General Samples: How similar and how different

MARKET AUDITS
11. Market Share Estimates and Their Standard Errors from Store Tests
21. How to Improve Test Marketing
22. An Examination of Weekend Audits

MEANS, ANALYSIS OF
4. Number-type Data: Structured vs. Open-ends
14. Analysis of Variance: One-factor Designs
17. Graphic Displays of Data: Box and Whisker Plots
18. Analysis of Ratios of Means
20. Examining Group Differences: Components of t- Plots
25. Function Plots of Multi-Dimensional Data
30. Testing Differences Among Several Means
37. Sample Sizes for Analyses of Means and Proportions
24. Interpretation of t-Test Results
48. An Alternative to the Mean

MEANS, FOR CENSORED SCALES
52. Censored Scales

MEDIANS
4. Number-type Data: Structured vs. Open-ends
17. Graphic Displays of Data: Box and Whisker Plots
48. An Alternative to the Mean

MINIMAX CRITERION
27. Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels

MULTINOMIAL DISTRIBUTION
26. Analysis of Forced-Choice Data

MULTIPLE COMPARISON PROCEDURE
14. Analysis of Variance: One-factor Designs
20. Examining Group Differences: Components of t- Plots
26. Analysis of Forced-Choice Data
30. Testing Differences Among Several Means
36. The Logic of Statistical Significance Tests

MULTIPLE PRODUCT QUESTIONNAIRE
12. Measuring Buying Intention: Product List vs. Single Product Questionnaire

MULTIPLE QUESTION ANSWER GRID
8. Using Multiple Question Grids

MULTIPLICITY
30. Testing Differences Among Several Means

MULTIVARIATE ANALYSIS
20. Examining Group Differences: Components of t- Plots
25. Function Plots of Multi-Dimensional Data
29. Displaying Group Differences Using Biplots

N

NO ANSWER, ANALYSIS OF NON-RESPONSE
12. Measuring Buying Intention: Product List vs. Single Product Questionnaire
-In Survey Data
8. Using Multiple Question Grids
23. Measuring Buying Intention: How Valid is the Estimate?
-To Rating Tasks
28. Measuring the "Importance" of Attributes

NULL HYPOTHESIS
36. The Logic of Statistical Significance Tests

O

ODDS
40. Measures of Relationship for Binary Data
55. Use of a Bayesian Orientation in Product Testing

ORDER ROTATION
1. An Examination of Order Bias (On self-administered questionnaires)

OUTLIERS
17. Graphic Displays of Data: Box and Whisker Plots

P

PAIRED COMPARISON PROCEDURE
-Attribute Evaluation
28. Measuring the "Importance" of Attributes

-Product Evaluation
19. Response Measures, Data Collection Methods, and Conjoint Analysis: A Two-attribute Case Study
26. Analysis of Forced-Choice Data
33. Simultaneous Measurement of Discrimination and Preference
38. Correctly Selecting the Best Product

PATTERN ANALYSIS
35. An Analysis of Multiple Brand Usage

PENALTY ANALYSIS
56. Triangle Plots: Graphic Display of "Just Right" Scale Data

PERCENTILES
17. Graphic Displays of Data: Box and Whisker Plots

PERCEPTUAL MAPS
27. Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels
29. Displaying Group Differences Using Biplots
53. The Effect of the Number of Scale Points in Measuring Product Perceptions

POWER (See Type II Error)
14. Analysis of Variance: One-factor Designs
27. Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels
36. The Logic of Statistical Significance Tests
37. Sample Sizes for Analyses of Means and Proportions
38. Correctly Selecting the Best Product
43. Balancing Confidence and Power for Decision Making

PREFERENCE
-Tests, Design Of
33. Simultaneous Measurement of Discrimination and Preference
41. Some Methodological Issues in Product Testing

-Influence By Attributes
15. Do You Want Overall Opinions or Diagnostic Information

-Measurement Of
35. An Analysis of Multiple Brand Usage
41. Some Methodological Issues in Product Testing

PRICE PERCEPTIONS
9. Pricing Research: Single vs. Multiple Presentations

PRIOR INFORMATION (see Bayesian inference)
55. Use of a Bayesian Orientation in Product Testing

PROBABILITY OF CORRECT SELECTION
38. Correctly Selecting the Best Product

PROBABILITY PLOT
17. Graphic Displays of Data: Box and Whisker Plots

PRODUCT LABELS, USE OF LETTERS
16. Using Letters to Identify Products or Brands

PRODUCT TESTS, ANALYSIS OF
55. Use of a Bayesian Orientation in Product Testing

PRODUCT TESTS, DESIGN STRUCTURE
16. Using Letters to Identify Products or Brands
33. Simultaneous Measurement of Discrimination and Preference
41. Some Methodological Issues in Product Testing
49. Statistical Designs for Ordering and Rotating Products in Product Tests
51. Factors Involved in Conducting Product Tests via Central Location Facilities

-Treatment Structure & Monadic For Ordering and Rotating Products
41. Some Methodological Issues in Product Testing

-Balanced Incomplete Block, Partially Balanced Incomplete Block, Factorial Design, Fractional Factorial Design, Latin Squares, Youden Squares, & Cross Over Design
41. Some Methodological Issues in Product Testing
49. Statistical Designs for Ordering and Rotating Products in Product Tests

PRODUCT TESTS, MEASUREMENT OF
-Absolute Measurement
-Relative or Comparative Measurement
-Direct vs. Indirect Measurement
43. Balancing Confidence and Power for Decision Making

PRODUCT TESTS, METHODS
51. Factors Involved in Conducting Product Tests via Central Location Facilities

PROPORTIONS, ANALYSIS OF
26. Analysis of Forced-Choice Data
37. Sample Sizes for Analyses of Means and Proportions
50. Statistical Analyses of Extreme Proportions
53. The Effect of the Number of Scale Points in Measuring Product Perceptions
54. Test of Differences Between Correlated Proportions

PURCHASE INCIDENCE, MEASUREMENT OF
5. Measuring Purchase Incidence Rates

PURCHASE INTENT
-Influenced By Multiple Product List
12. Measuring Buying Intention: Product List vs. Single Product Questionnaire

-Influenced By Price Presentation
9. Pricing Research: Single vs. Multiple Presentations

-Measurement Of
9. Pricing Research: Single vs. Multiple Presentations
12. Measuring Buying Intention: Product List vs. Single Product Questionnaire
23. Measuring Buying Intention: How Valid is the Estimate?

-Purchase Cycle
52. Censored Scales

-Validation Of Measures
23. Measuring Buying Intention: How Valid is the Estimate?

Q

QUESTIONNAIRE DESIGN
1. An Examination of Order Bias (On self-administered questionnaires)
4. Number-type Data: Structured vs. Open-ends
5. Measuring Purchase Incidence Rates
7. Frequency Measurement: Past vs. Average Period
8. Using Multiple Question Grids
9. Pricing Research: Single vs. Multiple Presentations
15. Do You Want Overall Opinions or Diagnostic Information
53. The Effect of the Number of Scale Points in Measuring Product Perceptions

R

RANK ORDER DATA
19. Response Measures, Data Collection Methods, and Conjoint Analysis: A Two-attribute Case Study
44. The Use of Concern Scales as an Alternative to Importance Ratings

RATING SCALES
-Analysis Of
2. Measuring Purchase Intent
-Censored
52. Censored Scales

-Comparison Of
2. Measuring Purchase Intent
3. Variations in Semantic Differential Scales
28. Measuring the "Importance" of Attributes
53. The Effect of the Number of Scale Points in Measuring Product Perceptions

-Concern Scales
44. The Use of Concern Scales as an Alternative to Importance Ratings

-Effect Of Context On
6. Brand Perceptions: Relative vs. Absolute Ratings

-Importance Scales
44. The Use of Concern Scales as an Alternative to Importance Ratings

-"Just Right"
56. Triangle Plots: Graphic Display of "Just Right" Scale Data

-Labeling Of Scale Points
28. Measuring the "Importance" of Attributes

-Semantics Of
2. Measuring Purchase Intent
3. Variations in Semantic Differential Scales

-Structure Of
2. Measuring Purchase Intent
3. Variations in Semantic Differential Scales
4. Number-type Data: Structured vs. Open-ends
28. Measuring the "Importance" of Attributes

-Transformation Of
2. Measuring Purchase Intent

-Variability Of Responses
37. Sample Sizes for Analyses of Means and Proportions

RATIO DATA
-Analysis Of
18. Analysis of Ratios of Means

-Measurement Of
4. Number-type Data: Structured vs. Open-ends

RECALL RESPONDENT
7. Frequency Measurement: Past vs. Average Period

REPEAT PAIR PROCEDURE
33. Simultaneous Measurement of Discrimination and Preference

RELATIVE EFFECT
57. Estimation of the Effect of Attributes on Overall Liking

RESPONSE PATTERNS
3. Variations in Semantic Differential Scales

S

SAMPLE SIZE ESTIMATION
14. Analysis of Variance: One-factor Designs
32. Estimating Sample Sizes for Mailouts
36. The Logic of Statistical Significance Tests
37. Sample Sizes for Analyses of Means and Proportions
38. Correctly Selecting the Best Product
45. Sample Size Tables For Significance Tests

-Effective Sample Size
-Finite Population Correction Factor (FPC)
47. The Effect of Population Size on Precision and Sample Size

SAMPLE SIZE TABLES
45. Sample Size Tables For Significance Tests

SAMPLING ERROR
37. Sample Sizes for Analyses of Means and Proportions

SAMPLING WITH REPLACEMENT (RESAMPLING)
31. Bootstrapping

SAMPLING
-Quota & Stratification
35. An Analysis of Multiple Brand Usage

-Mail Panels vs. General Samples
59. Mail Panels vs. General Samples: How similar and how different

SEGMENTATION
35. An Analysis of Multiple Brand Usage

SIGNIFICANCE LEVEL (See Type I Error, Confidence Level)
30. Testing Differences Among Several Means
36. The Logic of Statistical Significance Tests
37. Sample Sizes for Analyses of Means and Proportions

SIMILARITY COEFFICIENTS
35. An Analysis of Multiple Brand Usage

SKEWNESS
17. Graphic Displays of Data: Box and Whisker Plots

STANDARD ERROR
37. Sample Sizes for Analyses of Means and Proportions

STATISTICAL DECISION RULES
27. Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels

STATISTICAL SIGNIFICANCE TESTS
(See Specific Tests In Index)
11. Market Share Estimates and Their Standard Errors from Store Tests
13. Repeat Measures Design and Analysis
14. Analysis of Variance: One-factor Designs
18. Analysis of Ratios of Means
20. Examining Group Differences: Components of t- Plots
24. Interpretation of t-Test Results
26. Analysis of Forced-Choice Data
27. Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels
32. Estimating Sample Sizes for Mailouts
34. Confidence and Tolerance Intervals
36. The Logic of Statistical Significance Tests
37. Sample Sizes for Analyses of Means and Proportions
38. Correctly Selecting the Best Product
54. Test of Differences Between Correlated Proportions

STRUCTURED VS. UNSTRUCTURED QUESTIONS

4. Number-type Data: Structured vs. Open-ends
7. Frequency Measurement: Past vs. Average Period

SUBJECTIVE PRIOR PROBABILITIES
27. Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels

T

TASTE TEST
51. Factors Involved in Conducting Product Tests via Central Location Facilities

t-Test
18. Analysis of Ratios of Means
20. Examining Group Differences: Components of t-Plots
24. Interpretation of t-Test Results

TELEPHONE SAMPLING
-Raised Integer Dialing, Random Digit Dialing (RDD), & Systematic Digit Dialing
10. Dialing Selection Techniques: Random Digit vs. Directory
TEST MARKETING
21. How to Improve Test Marketing
22. An Examination of Weekend Audits

TOLERANCE INTERVAL
34. Confidence and Tolerance Intervals

TRIAD PROCEDURE & TRIANGLE DISCRIMINATION PROCEDURE
33. Simultaneous Measurement of Discrimination and Preference

TRIANGLE PLOTS
56. Triangle Plots: Graphic Display of "Just Right" Scale Data

TYPE I ERROR (See Significance Level, Confidence Level)
27. Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels
30. Testing Differences Among Several Means
36. The Logic of Statistical Significance Tests
37. Sample Sizes for Analyses of Means and Proportions
38. Correctly Selecting the Best Product
43. Balancing Confidence and Power for Decision Making
55. Use of a Bayesian Orientation in Product Testing

TYPE II ERROR (See Power)
27. Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels
36. The Logic of Statistical Significance Tests
37. Sample Sizes for Analyses of Means and Proportions
38. Correctly Selecting the Best Product
43. Balancing Confidence and Power for Decision Making
55. Use of a Bayesian Orientation in Product Testing

U

UNIT OF ANALYSIS
11. Market Share Estimates and Their Standard Errors from Store Tests

V

VARIABILITY
17. Graphic Displays of Data: Box and Whisker Plots

VARIANCE, ESTIMATION OF
37. Sample Sizes for Analyses of Means and Proportions

VARIANCE, WITH CENSORED SCALES
52. Censored Scales

VERSIONING, EFFECT ON RATINGS
6. Brand Perceptions: Relative vs. Absolute Ratings

W

WEEKEND AUDITS
22. An Examination of Weekend Audits

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