Engineers, Six Sigma practitioners, and other researchers often work with "hard" data - discrete data that can be counted and legitimately expressed as ratios. But what of "soft" data, things like opinions, attitudes, satisfaction? Can statistical process controls (SPC) be applied here? Can process variation in customer satisfaction, for example, be measured and then reported to management in a meaningful way? Can we leverage "appeal", "responsiveness", or "value for money spent"?
Oracle Crystal Ball is the leading spreadsheet-based application suite for predictive modeling, forecasting, simulation, and optimization. It gives you unparalleled insight into the critical factors affecting risk. With Crystal Ball, you can make the right tactical decisions to reach your objectives and gain a competitive edge under even the most uncertain market conditions.
Arguably the most successful SPC tool is the control chart, originally developed by Walter Shewhart in the early 1920s. A control chart helps you record data and lets you see when an unusual event, e.g., a very high or low observation compared with “typical” process performance, occurs.
This page includes information and resources on Pearson's Correlation Coefficient or Pearson's r, Chi-Square, t-tests, including the One-Sample t-test, the Independent Samples t-test, and the Dependent Samples t-test, and the ANOVA, or Analysis of Variance.
This Web site is a course in statistics appreciation; i.e., acquiring a feeling for the statistical way of thinking. It contains various useful concepts and topics at many levels of learning statistics for decision making under uncertainties. The cardinal objective for this Web site is to increase the extent to which statistical thinking is merged with managerial thinking for good decision making under uncertainty.