Exploring, Displaying, and Examining Data

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17-1 © 2006 The McGraw-Hill Companies, Inc., All Rights Reserved. McGraw-Hill/Irwin Chapter Chapter 17 17 Exploring, Exploring, Displaying, Displaying, and and Examining Examining Data Data

description

Research Management chapter 17,Explains the various methods for exploring displaying and examining data.

Transcript of Exploring, Displaying, and Examining Data

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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

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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