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Data "Sanity": The Need for Statistical Thinking in Everyday Work
Summary: A quality improvement context invalidates many assumptions perpetuated through traditional, research-oriented university statistical courses - hence rendering many common analyses inappropriate! Resulting stigma from such past, usually mandated, courses also represents a formidable cultural barrier to the effective data collection, analysis and results-implementation so necessary to improvement.
This all-day seminar will introduce a deceptively simple, elegant - and initially quite counter-intuitive - approach to statistics as an organizational framework for expanding improvement efforts.
Outline of course content:
- You are already using statistics - Recognizing poor and ineffective data displays,
- Implicit assumptions of "traditional" statistics - Research vs. Quality Improvement - and the need for process-oriented thinking... including the data process,
- The issue of "sample size" is moot,
- A "series of meetings" based on real data from commonly-encountered situations to gain insight into eight hidden organizational statistical "traps" and facility in simple run charts, control charts, and p-charts for understanding:
- The deceptiveness of percentage data,
- The danger of arbitrary numerical goals and rankings,
- Proper meanings of the terms "trend," "above average," and "below average,"
- The power of simply "plotting the dots" to assess Common & Special causes impairing process predictability,
- The art of asking more incisive questions.
Format of session: Lecture (35%), intense dialogue (30%), and participant small-group work (35%)
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