Chapter 1: Data Analysis for Improved Decision Making    1

Introduction    1
Types of Problems:  Disturbance vs. Opportunity    2
Mental Models and Effective Problem Solving: Verbal and/or Visual    2
Types of Variation: Common-Cause vs. Assignable Cause    4
Types of Data Business Professionals Use: Cross-Sectional vs. Time Series    8
Data Measurement Scales: Ratio, Interval, Ordinal, Nominal    10
Data Sources for Improved Decision Making:  Have it, make it, buy it    12
Data Collection through Surveys: 
    Target Population: all people who will actuallyvote  13
    Sampling Frame: all people with listed telephone numbers  13
    Sampling Design  13
            Nonrandom samples: Convenience samples, Jusgmental samples
            Randomized Cluster Sampling
            Stratified Random Sampling
            Simple Random Sampling
                    Sample Size
                            depends strongly on population variability and desired precicion and confidence
                            almost independent of population size
    Survey Design   14
            Personal Interviews
            Telephone Interviews
            Mail and Email Questionnaires
            Web Based surveys
Summary    16
Exercises    16
Appendices    21