2. Part Four ANALYSIS AND PRESENTATION OF DATA
McGraw-Hill/Irwin
© 2003 The McGraw-Hill Companies, Inc.,All Rights Reserved.

3. Chapter Sixteen EXPLORING, DISPLAYING, AND EXAMINING DATA

4. 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

5. Techniques to Display and Examine Distributions
Frequency Table
Visual Displays
Histograms
Stem-and-leaf display
Box-plot
Crosstabulation of Variables

6. 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

7. 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

8. 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

9. 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

10. 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

11. Geographic Information Systems
Systems of hardware, software, and procedures that capture, store, manipulate, integrate, and display spatially-referenced data

12. Geographic Information Systems
Minimum four components
Integrating information from various sources
Capturing data
Projection and restructuring
Modeling

13. Crosstabulation A technique for comparing two classification variables
Cells
Marginals
Contingency tables

14. Percentaging Errors Averaging percentages without weighting
Using too-large percentages (>100%)
Using percentage with very small sample
Citing percentage decrease exceeding 100 percent

15. 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.