1. Chapter XIV
Data Preparation

2. Chapter Outline 1) Overview 2) The Data Preparation Process
3) Questionnaire Checking
4) Editing
i. Treatment of Unsatisfactory Responses
5) Coding
i. Coding Questions
ii. Code-book
iii. Coding Questionnaires 1

3. ii. Treatment of Missing Responses 8) Statistically Adjusting the Data
6) Transcribing
7) Data Cleaning
i. Consistency Checks
ii. Treatment of Missing Responses
8) Statistically Adjusting the Data
i. Weighting
ii. Variable Respecification
iii. Scale Transformation
9) Selecting a Data Analysis Strategy
Adjusting the Data 1

4. 10) A Classification of Statistical Techniques
11) Ethics in Marketing Research
12) Internet & Computer Applications
13) Focus on Burke
14) Summary
15) Key Terms and Concepts
16) Acronyms 1

5. Data Preparation Process
Fig. 14.1
Prepare Preliminary Plan of Data Analysis
Check Questionnaire
Edit
Code
Transcribe
Clean Data
Statistically Adjust the Data
Select Data Analysis Strategy

6. An Illustrative Computer File
Table 14.1
Fields
Column Numbers
Records
Record
Record
Record
Record
Record

7. Keypunching via CRT Terminal Computerized Sensory Analysis
Data Transcription
Fig. 14.4
Raw Data
CATI/ CAPI
Keypunching via CRT Terminal
Mark Sense Forms
Optical Scanning
Computerized Sensory Analysis
Verification:Correct Keypunching Errors
Computer
Disks
Magnetic Tapes
Memory
Transcribed Data

8. Selecting a Data Analysis Strategy
Fig. 14.5
Earlier Steps (1,2, & 3) of the Marketing Research Process
Known Characteristics of the Data
Properties of Statistical Techniques
Background and Philosophy of the Researcher
Data Analysis Strategy

9. Univariate Techniques
A Classification of Univariate Techniques
Fig. 14.6
Univariate Techniques
Metric Data
Non-numeric Data
One Sample
Two or More Samples
One Sample
Two or More Samples
* t test
* Z test
Frequency
Chi-Square
K-S
Runs
Binomial
Independent
Related
* Two- Groupt test
* Z test
* One-Way ANOVA
* Paired
* t test
Independent
Related
* Chi-Square
* Mann-Whitney
* Median
* K-S
* K-W ANOVA
* Sign
* Wilcoxon
* McNemar
* Chi-Square

10. A Classification of Multivariate Techniques
Fig. 14.7
Multivariate Techniques
Dependence Technique
Interdependence Technique
One Dependent Variable
More Than One Dependent Variable
Variable Interdependence
Interobject Similarity
* Cross- Tabulation
* Analysis of Variance and Covariance
* Multiple Regression
* Conjoint Analysis
* Multivariate Analysis of Variance and Covariance
* Canonical Correlation
* Multiple Discriminant Analysis
* Factor Analysis
* Cluster Analysis
* Multidimensional Scaling

11. Nielsen’s Internet Survey: “Does It Carry Any Weight?”
RIP14.1
The Nielsen Media Research Company, a longtime player in television-related marketing research has come under fire from the various TV networks for its surveying techniques. Additionally, in another potentially large, new revenue business, Internet surveying, Nielsen is encountering serious questions concerning the validity of its survey results. Due to the tremendous impact of electronic commerce on the business world, advertisers need to know how many people are doing business on the Internet in order to decide if it would be lucrative to place their ads online.
Nielsen performed a survey for CommerceNet, a group of companies that includes Sun Microsystems and American Express, to help determine the number of total users on the Internet.

12. Nielsen’s research stated that 37 million people over the age of 16 have access to the Internet and 24 million have used the Net in the last three months. Where statisticians believe the numbers are flawed is in the weighting used to help match the sample to the population. Weighting must be used to prevent research from being skewed towards one demographic segment.

13. The Nielsen survey was weighted for gender but not for education which may have skewed the population towards educated adults. Nielsen then proceeded to weight the survey by age and income after they had already weighted it for gender. Statisticians also feel that this is incorrect because weighting must occur simultaneously, not in separate calculations. Nielsen does not believe the concerns about their sample are legitimate and feel that they have not erred in weighting the survey. However, due to the fact that most third parties have not endorsed Nielsen’s methods, the validity of their research remains to be established.