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Tools & Techniques of Data Analysis

presented by Burke Institute
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Bring a trainer to your location to deliver this class for groups of 10 or more.

Summary

This intensive seminar uses a step by step procedure composed of several decision flow charts to help you select and implement the correct statistical techniques for your problems

Workshop Description/Agenda

WHAT YOU WILL LEARN

  • How to develop an analysis plan for a study by linking management decisions and information needs to the available data.
  • How to choose the best univariate, bivariate or multivariate statistical techniques to analyze data from virtually any marketing research study.
  • How to summarize marketing research data and translate it into decision making information.
  • What statistical significance tests do, how to choose the right one, how to interpret typical computer output and how to relate the results to the marketing questions.
  • How to compute sample size.
  • How to select the best procedure for determining associations among marketing variables and how to interpret and use correlation coefficients.
  • How to clean and weight the data so that you can trust the results and act with the data

WORKSHOP AGENDA

SESSION 1: BUILDING THE CASE FOR HOW TO BEST ANALYZE RESEARCH DATA

  • Case study examples of improper/deceptive manipulations of data and their consequences
  • How to interpret the data from the case studies
  • Common errors made in data tabulations, summary measures and other analytical procedures and how to avoid them

SESSION 2: FUNDAMENTAL PRINCIPLES FOR ANALYZING DATA

  • Purpose and goal of data analysis
  • Data analysis impact on research design
  • Characteristics of data and other considerations required for selecting the best analytical procedure for each situation

SESSION 3: STEP-BY-STEP GUIDELINES FOR SELECTING THE BEST ANALYTICAL TOOL

  • Integrated flowcharts for choosing the best analytical tool
  • Workshop using the flowcharts to apply the tools to a wide variety of situations commonly encountered in marketing research, such as:
    • Summarizing research data and stat testing
    • Deciding when to use t, chi square, f and other tests
    • Choosing correlational procedures and deciding when to use factor, cluster, conjoint, regression, and other multivariate techniques

SESSION 4: UNDERSTANDING CROSSTABS AND DATA WEIGHTING ISSUES

  • Using crosstabs to analyze data
  • How to avoid common mistakes with tabular data
  • Common procedures for weighting data
  • Practical guidelines for getting the most out of crosstabs

SESSION 5: SUMMARY MEASURES FOR RESEARCH DATA

  • Use and misuse of various measures of average and dispersion
  • Practical guidelines for the proper interpretation of mean, weighted mean, median, standard deviation, variance and other measures
  • Confidence interval estimation -- what is it, what does it do and what is it used for?
  • Procedures for computing sample size under a variety of conditions encountered in marketing research

SESSION 6: STATISTICAL SIGNIFICANCE TESTING

  • The framework for significance testing
  • Cautions in interpreting results from tests of significance
  • Key decisions in significance testing, one-tailed vs. two-tailed tests, confidence vs. significance level and other considerations
  • Description of procedures for analyzing nominal, ordinal and metric data from panels, preference evaluations, purchase likelihood, tracking studies, product testing, advertising awareness and other studies

SESSION 7: ANALYSIS OF ASSOCIATIONS IN RESEARCH DATA

  • Bivariate correlation procedures for various types of research data
  • When to use and how to interpret each coefficient
  • Key terms and definitions for correlation analysis
  • Association case studies and computer output examples

Who Should Attend

Marketing Research Professionals

Additional Information

Training Provider: Burke Institute

Course Topics: Marketing Training > Marketing Research

Training Course Summary: This intensive seminar uses a step by step procedure composed of several decision flow charts to help you select and implement the correct statistical techniques for your problems