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16-2McGraw-Hill/Irwin © 2003 The McGraw-Hill Companies, Inc.,All Rights

Reserved.

Part FourANALYSIS AND

PRESENTATION OF DATA

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Chapter SixteenEXPLORING, DISPLAYING,

AND EXAMINING DATA

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Types of Data Analysis

• Exploratory data analysis– the data guide the choice of analysis--or a

revision of the planned analysis

• Confirmatory data analysis– closer to classical statistical inference in its

use of significance and confidence– may use information from a closely related

data set or by validating findings through the gathering and analyzing of new data

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Techniques to Display and Examine Distributions

• Frequency Table

• Visual Displays– Histograms

– Stem-and-leaf display

– Box-plot

• Crosstabulation of Variables

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Techniques to Display and Examine Distributions

• Histograms– Display all intervals in a distribution, even

without observed values– Examine the shape of the distribution for

skewness, kurtosis, and the modal pattern

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Techniques to Display and Examine Distributions (cont.)

• Box-plot (box and whisker-plot)– Rectangular plot encompasses 50% of

the data values• Edges of the box (hinges)

– Center line through the width of the box marks the median

– Whiskers extend from the right and left hinges to the largest and smallest values

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Techniques to Display and Examine Distributions (cont.)

• Transformation– To improve interpretation and

compatibility with other data sets

– To enhance symmetry and stabilize spread

– To improve linear relationships between and among variables

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Improvement & Control Analysis

• Statistical process control– Uses statistical tools to analyze, monitor,

and improve process performance– Total Quality Management– Control chart

• Displays sequential measurements of a process together with a center line and control limits

– Upper control limit

– Lower control limit

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Types of Control Charts

• Variables data

(ratio or interval measurements)– X-bar– R-charts– s-charts– Pareto Diagrams

• Bar chart whose percentages sum to 100 percent

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Geographic Information Systems

• Systems of hardware, software, and procedures that capture, store, manipulate, integrate, and display spatially-referenced data

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Geographic Information Systems

• Minimum four components– Integrating information from various

sources– Capturing data– Projection and restructuring– Modeling

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Crosstabulation

• A technique for comparing two classification variables– Cells– Marginals– Contingency tables

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Percentaging Errors

• Averaging percentages without weighting

• Using too-large percentages (>100%)

• Using percentage with very small sample

• Citing percentage decrease exceeding 100 percent

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Other Table-based Analysis

• Automatic Interaction Detection (AID)– Sequential partitioning procedure that uses a

dependent variable and set of predictors– Searches among up to 300 variables for the

best single division of data into subsets according to each predictor variable,

– Chooses one division approach – Splits the sample using chi-square tests to

create multi-way splits.