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Chapter 16 Chapter 16 Exploring, Displaying, Exploring, Displaying, and Examining Data and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.
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Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

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Page 1: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

Chapter 16Chapter 16

Exploring, Displaying, Exploring, Displaying, and Examining Dataand Examining Data

McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved. 

Page 2: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-2

Learning ObjectivesLearning 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.

Page 3: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

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Research as Research as Competitive AdvantageCompetitive Advantage

“As data availability continues to increase, theimportance of identifying/filtering and analyzingrelevant data can be a powerful way to gain aninformation advantage over our competition.”

Tom H.C. Anderson founder & managing partner

Anderson Analytics, LLC

Page 4: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

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PulsePoint: PulsePoint: Research RevelationResearch Revelation

65 The percent boost in company revenue created by best practices in data quality.

Page 5: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-5

Researcher Skill Improves Data Researcher Skill Improves Data DiscoveryDiscovery

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 a template process.

Page 6: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

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Exploratory Data AnalysisExploratory Data Analysis

ConfirmatoryExploratory

Page 7: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

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Data Exploration, Examination, Data Exploration, Examination, and Analysis in the Research and Analysis in the Research ProcessProcess

Page 8: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-8

Research Values the Research Values the UnexpectedUnexpected

“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, authorInnovation and Entrepreneurship

Page 9: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-9

Frequency of Ad RecallFrequency of Ad Recall

Value Label Value Frequency Percent Valid Cumulative Percent Percent

Page 10: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-10

Bar ChartBar Chart

Page 11: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-11

Pie ChartPie Chart

Page 12: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-12

Frequency TableFrequency Table

Page 13: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-13

Histogram Histogram

Page 14: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-14

Stem-and-Leaf DisplayStem-and-Leaf Display

455666788889

12466799

02235678

02268

24

018

3

1

06

3

36

3

6

8

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

Page 15: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

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Pareto DiagramPareto Diagram

Page 16: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-16

Boxplot ComponentsBoxplot Components

Page 17: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-17

Diagnostics with BoxplotsDiagnostics with Boxplots

Page 18: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-18

Boxplot ComparisonBoxplot Comparison

Page 19: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-19

MappingMapping

Page 20: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-20

Geograph: Geograph: Digital Camera OwnershipDigital Camera Ownership

Page 21: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-21

SPSS Cross-TabulationSPSS Cross-Tabulation

Page 22: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-22

Percentages in Percentages in Cross-TabulationCross-Tabulation

Page 23: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-23

Guidelines for Using Guidelines for Using PercentagesPercentages

Averaging percentagesAveraging percentages

Use of too large percentagesUse of too large percentages

Using too small a baseUsing too small a base

Percentage decreases can never exceed 100%

Percentage decreases can never exceed 100%

Page 24: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-24

Cross-Tabulation with Control Cross-Tabulation with Control and Nested Variablesand Nested Variables

Page 25: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-25

Automatic Interaction Detection Automatic Interaction Detection (AID)(AID)

Page 26: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

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Exploratory Data Analysis 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.

Page 27: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

16-27

Key TermsKey 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

Page 28: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

Working with

Data Tables

McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved. 

Page 29: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

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Original Data TableOriginal Data Table

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

Page 30: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

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Arranged by SpendingArranged by Spending

Page 31: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

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Arranged by Arranged by No. of PurchasesNo. of Purchases

Page 32: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

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Arranged by Avg. Transaction, Arranged by Avg. Transaction, HighestHighest

Page 33: Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved.

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Arranged by Avg. Transaction, Arranged by Avg. Transaction, LowestLowest