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EXPLORING, 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.