Exploring, Displaying, and Examining Data Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Business Research Methods, 10e Copyright © 2008 by The McGraw-Hill Companies, Inc. All Rights Reserved.

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.

PulsePoint: Research Revelation 67 The percent of college students who see nothing unethical about swapping or downloading digital copyrighted files (software, music, movies) without paying for them.

Research Values the Unexpected “It is precisely because the unexpected jolts us out of our preconceived notions, our assumptions, our certainties, that it is such a fertile source of innovation.” Peter Drucker, author Innovation and Entrepreneurship

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.

Exploratory Data Analysis Confirmatory

Data Exploration, Examination, and Analysis in the Research Process

Frequency of Ad Recall Value Label Value Frequency Percent Valid Cumulative Percent Percent

Bar Chart

Pie Chart

Frequency Table

Histogram

Stem-and-Leaf Display 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 455666788889 12466799 02235678 02268 24 018 3 1 06 36 6 8

Pareto Diagram

Boxplot Components

Diagnostics with Boxplots

Boxplot Comparison

Mapping

Geograph: Digital Camera Ownership

SPSS Cross-Tabulation

Percentages in Cross-Tabulation

Guidelines for Using Percentages Averaging percentages Use of too large percentages Using too small a base Percentage decreases can never exceed 100%

Cross-Tabulation with Control and Nested Variables

Automatic Interaction Detection (AID)

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.

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

Working with Data Tables

Our grateful appreciation to eMarketer for the use of their table. Original Data Table Our grateful appreciation to eMarketer for the use of their table.

Arranged by Spending

Arranged by No. of Purchases

Arranged by Avg. Transaction, Highest

Arranged by Avg. Transaction, Lowest