McGraw-Hill/Irwin Business Research Methods, 10eCopyright © 2008 by The McGraw-Hill Companies, Inc. All Rights Reserved. Chapter 16 Exploring, Displaying, and Examining Data
16-2 Learning Objectives Understand... That exploratory data analysis techniques provide insights and data diagnostics by emphasizing visual representations of the data. How cross-tabulation is used to examine relationships involving categorical variables, serves as a framework for later statistical testing, and makes an efficient tool for data visualization and later decision-making.
16-3 Researcher Skill Improves Data Discovery DDW is a global player in research services. As this ad proclaims, you can “push data into a template and get the job done,” but you are unlikely to make discoveries using that process.
16-4 Exploratory Data Analysis ConfirmatoryExploratory
16-5 Data Exploration, Examination, and Analysis in the Research Process
16-6 Frequency of Ad Recall Value Label Value Frequency Percent Valid Cumulative Percent Percent
16-7 Bar Chart
16-8 Pie Chart
16-9 Frequency Table
16-10 Histogram
16-11 Stem-and-Leaf Display
16-12 Pareto Diagram
16-13 Boxplot Components
16-14 Diagnostics with Boxplots
16-15 Boxplot Comparison
16-16 Mapping
16-17 Geograph: Digital Camera Ownership
16-18 SPSS Cross-Tabulation
16-19 Percentages in Cross-Tabulation
16-20 Guidelines for Using Percentages Averaging percentages Use of too large percentages Using too small a base Percentage decreases can never exceed 100%
16-21 Cross-Tabulation with Control and Nested Variables
16-22 Automatic Interaction Detection (AID)
16-23 Exploratory Data Analysis This Booth Research Services ad suggests that the researcher’s role is to make sense of data displays. Great data exploration and analysis delivers insight from data.
16-24 Key Terms Automatic interaction detection (AID) Boxplot Cell Confirmatory data analysis Contingency table Control variable Cross-tabulation Exploratory data analysis (EDA) Five-number summary Frequency table Histogram Interquartile range (IQR) Marginals Nonresistant statistics Outliers Pareto diagram Resistant statistics Stem-and-leaf display
McGraw-Hill/Irwin Business Research Methods, 10eCopyright © 2008 by The McGraw-Hill Companies, Inc. All Rights Reserved. Working with Data Tables 1-25
16-26 Original Data Table Our grateful appreciation to eMarketer for the use of their table.
16-27 Arranged by Spending
16-28 Arranged by No. of Purchases
16-29 Arranged by Avg. Transaction, Highest
16-30 Arranged by Avg. Transaction, Lowest