This book presents guidelines for the development and evaluation of statistical software designed to ensure minimum acceptable statistical functionality as well as ease of interpretation and use. It consists of the proceedings of a forum that focused on three qualities of statistical software: richness—the availability of layers of output sophistication, guidance—how the package helps a user do an analysis and do it well, and exactness—determining if the output is "correct" and when and how to warn of potential problems.
- THE FUTURE OF STATISTICAL SOFTWARE
- Copyright
- Preface
- Contents
- Morning Session Opening Remarks
- Richness for the One-Way ANOVA Layout
- STATEMENT OF THE PROBLEM
- Rationale of Approach
- Problem Boundaries.
- RICHNESS DIMENSIONS
- 1. Epistemological Goals
- 2. Methods
- 3. Inputs
- 4. Outputs
- 5. Options
- 6. Structure
- 7. Internal Paths.
- 8. External Paths
- 9. Documentation
- 10. Audiences
- WHAT NEXT?
- Step Back
- Jump In (Continuous Involvement)
- REFERENCES
- Serendipitous Data and Future Statistical Software.
- WHERE IS STATISTICAL SOFTWARE GOING?
- INNOVATIONS IN COMPUTING WILL OFFER NEW OPPORTUNITIES
- CHALLENGES FOR STATISTICAL SOFTWARE
- IS THE COMMERCIAL MARKETPLACE THE BEST SOURCE OF STATISTICAL SOFTWARE INNOVATION?
- WHAT CAN WE DO TO ENCOURAGE INNOVATION?
- WHAT CAN WE DO TO ENSURE QUALITY?
- WHAT CAN WE DO TO PROMOTE PROGRESS?
- REFERENCES.
- Morning Discussion
- Afternoon Session Opening Remarks
- An Industry View
- INTRODUCTION
- REQUIREMENTS FOR “INDUSTRIAL-GRADE” SOFTWARE
- IMPLICATIONS FOR RICHNESS.
- IMPLICATIONS FOR GUIDANCE
- CONCLUSION
- Guidance for One-Way ANOVA
- GOALS OF GUIDANCE
- PHILOSOPHY OF GUIDANCE
- RECOGNIZING THE ONE-WAY ANOVA PROBLEM
- ADAPTIVE FITTING PROCEDURE
- GUIDANCE FOR INTERPRETATION.
- GUIDANCE FOR REPORT WRITING
- GUIDANCE REGARDING TACIT TECHNICAL ASSUMPTIONS
- Adjusting for Unequal Dispersions
- Adjusting for Outlier-prone Data
- Incorporating Statistical Expertise into Data Analysis Software
- OVERVIEW
- WHAT IS MEANT BY STATISTICAL EXPERTISE?
- WHO NEEDS SOFTWARE WITH STATISTICAL EXPERTISE?
- LIMITATIONS TO THE INCORPORATION OF STATISTICAL EXPERTISE
- EFFORTS TO BUILD DATA ANALYSIS SOFTWARE
- REX
- Student
- TESS
- General Observations on TESS and Student
- Mini-expert Functions
- CONCLUDING OBSERVATIONS
- REFERENCES.
- Afternoon Discussion
- Closing Remarks
- Appendixes
- Appendix A Speakers
- Keith E. Muller
- Paul F. Velleman
- Andrew Kirsch
- William DuMouchel
- Daryl Pregibon
- Appendix B Position Statements: Additional Material Submitted by Symposium Participants
- R. Clifton Bailey
- References
- Michael P. Cohen.
- James R. Knaub, Jr.
- Reference
- Jay Magidson
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