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In this 2-day introductory data analysis seminar, designed to help you translate marketing research data into decision making information, you will learn:
  • 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

----- First Day -----

08:30 AM - 08:45 AM Introduction of Participants

08:45 AM - 10:15 AM Session 1
    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

     

10:15 AM - 10:30 AM Break

 

10:30 AM - 12:00 PM Session 2
    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

     

12:00 PM - 01:15 PM Lunch Break

 

01:15 PM - 03:15 PM Session 3
    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
03:15 PM - 03:30 PM Break

 

03:30 PM - 04:30 PM Session 4
    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

     

04:30 PM - 05:00 PM Session 5
    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

     

----- Second Day -----

08:30 AM - 10:15 AM Session 6
    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
10:15 AM - 10:30 AM Break

 

10:30 AM - 12:00 PM Session 7
    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

     

12:00 PM - 01:15 PM Lunch Break

 

01:15 PM - 02:45 PM Session 8
    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

     

02:45 PM - 03:00 PM Break

 

03:00 PM - 04:30 PM Session 9
    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
04:30 PM - 04:45 PM Concluding Remarks
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