exploring, displaying, and examining data
DESCRIPTION
Research Management chapter 17,Explains the various methods for exploring displaying and examining data.TRANSCRIPT
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© 2006 The McGraw-Hill Companies, Inc., All Rights Reserved.
McGraw-Hill/Irwin
Chapter 17Chapter 17
Exploring, Exploring, Displaying, and Displaying, and Examining DataExamining Data
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Learning Objectives
Understand . . .• 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
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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
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Data Analysis
ConfirmatoryExploratory
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Exhibit 17-1 Data Exploration, Examination, and Analysis in the Research Process
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Exhibit 17-2 Frequency of Ad Recall
Value Label Value Frequency Percent Valid Cumulative Percent Percent
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Exhibit 17-3 Pie Chart
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Exhibit 17-3 Bar Chart
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Exhibit 17-4 Frequency Table
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Exhibit 17-5 Histogram
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Exhibit 17-6 Stem-and-Leaf Display
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455666788889
12466799
02235678
02268
24
018
3
1
06
3
36
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8
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Exhibit 17-7 Pareto Diagram
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Exhibit 17-8 Boxplot Components
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Exhibit 17-9 Diagnostics with Boxplots
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Exhibit 17-10 Boxplot Comparison
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Mapping
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Digital Camera Map
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Exhibit 17-11 SPSS Cross-Tabulation
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Exhibit 17-12 Percentages in Cross-Tabulation
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Guidelines for Using Percentages
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%
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Exhibit 17-13 Cross-Tabulation with Control and Nested
Variables
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Exhibit 17-14 AID Example
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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