The Fundamentals of Data Analysis: Preparing, Weighting, Analyzing (DA01)
Details
- How to construct, prepare, analyze and summarize research data.
- How to synthesize data from multiple sources and then utilize proper analysis methods.
- What "Big Data" is all about and insights on how to integrate with your research data.
- How apply proper weighting procedures and avoid common analytical pitfalls when analyzing research data.
- What various summary statistics such as median, standard deviation, and standard error mean and how to use them.
- How to use crosstabs and other analytical procedures to turn research data into actionable information.
- How to develop an analysis plan to link research data to specific marketing questions.
- How to explain results from marketing research studies to decision makers.
Outline
08:30 AM - 08:45 AM Introduction of Participants
08:45 AM - 10:15 AM Session 1
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DATA ANALYSIS IN MARKETING RESEARCH:
- Types of analysis commonly performed in marketing research including cross-tabs, summary statistics, significance tests, and correlations
- Improper manipulations and their consequences
- Developing a tab/analysis plan
10:30 AM - 12:00 PM Session 2
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QUALITY DATA REQUIRES PLANNING AND PREPARATION:
- Preparation of research data
- Guidelines for precoding open and closed ended questionnaires
- Computer output and a questionnaire illustrating pre- and post-coding
- Editing data and procedures for dealing with missing information
01:15 PM - 03:15 PM Session 3
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FUNDAMENTAL ANALYSIS OF RESEARCH DATA:
- Marginal, cumulative and cross tabulation of data
- How to interpret computer printout
- Terminology used in tabulations
- Typical cross-tab formats used in marketing research
- Specialized cross-tabs such as the turnover table
- Cleaning up the cross-tab
03:30 PM - 04:30 PM Session 4
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COMMON PROBLEMS / DECISIONS IN DATA ANALYSIS:
- Key issues: Direction of percentaging, multiway tabulations, the base for percentaging, and the interpretation of the total column
- Weighting and sample balancing, why use it and how to do it
- Commercially available cross-tab software and illustrative output
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BIG DATA:
- What is big data, where did it come from and why you should care
- Assembling, storing and analyzing big data
- Organizational implications of big data
- Illustrative output
08:30 AM - 10:15 AM Session 6
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MEASURES FOR SUMMARIZING RESEARCH DATA:
- Proper use of mean, median, and mode
- When to use which and why
- Measurement scales and the appropriateness of various summary statistics
- Interpreting computer printout
10:30 AM - 12:00 PM Session 7
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SPECIALIZED MEASURES FOR SUMMARIZING RESEARCH DATA:
- Cautions and guidelines for computing averages for grouped data
- Interpreting computer output
- Weighted means, why and how
- Computing average rates of growth
- Other averages for nominal, ordinal and metric data
01:15 PM - 02:45 PM Session 8
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MEASURES FOR ASSESSING THE DISPERSION IN RESEARCH DATA:
- Standard deviation, variance, range and other measures of dispersion
- Standard error, what is it, and how to use it
- Standardized scores and their application in marketing research
- Interpreting computer printout
03:00 PM - 04:30 PM Session 9
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STATISTICAL INFERENCE:
- Basic concepts underlying statistical description and inference
- Confidence interval estimates and the range of error
- Selecting and using appropriate significance tests
- Interpreting computer output
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