The Burke Institute presents
 

Tools & Techniques of Data Analysis On-Site Training

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

Course 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

More Seminar Information

The Burke Institute Delivery Method  On-Site Training