Data 'Sanity': Statistical Thinking Applied to Everyday Data
Abstract: This publication exposes eight common statistical "traps". They are: 1. Treating all observed variation in a time series data sequence as special causes, 2. Fitting inappropriate "trend" lines to a time series data sequence, 3. Unnecessary obsession with and incorrect application of the Normal distribution, 4. Incorrect calculation of standard deviation and "sigma" limits, 5. Misreading special cause signals on a control chart, 6. Choosing arbitrary cutoffs for "above" average and "below" average, 7. Improving processes through arbitrary numerical goals and standards, 8. Using statistical techniques on "rolling" or "moving" averages.
Keywords: Process-oriented thinking - Time Series Data - Variance Reduction