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Practitioners may encounter metrics with physical limits, where the distribution is truncated at the value of physical limitation. In these situations, estimating the population's standard deviation for the normal distribution can aid in analysis.
A variety of analyses can be done during the Analyze phase of a Six Sigma software project with data from Fagan-style inspections. These analyses suggest possible implications when considering Improve activities.
For short-term forecasting, Black Belts can benefit from analyzing moving average plots and looking for special causes of variation. When making long-term forecasts, a method that uses a normal curve and Z-scores may be the better bet.
Before proceeding with probability models, inference or descriptive statistics, the question of homogeneity whether a collection of observations can be assumed to have come from one population must first be addressed.
The cookbook contains a succinct representation of various topics in probability theory and statistics. It provides a comprehensive reference reduced to the mathematical essence, rather than aiming for elaborate explanations.
The desirability function can be used to prove Ron Santo's right to a spot in the baseball Hall of Fame, as well as to determine how well certain variables are meeting customer needs, and is therefore an important skill for Six Sigma practitioners.
Finding the most cost-effective way for Micropump to obtain the clean and reliable data needed to drive its Lean Six Sigma projects has helped the company accelerate innovations in its product line and consequently improved its bottom line.
Part 2 describes some statistical tools practitioners can use for predictive decision making.
Part 1 of this article will help practitioners understand the key drivers for the growth of statistics and introduce some leading analytics competitors.
To interpret data, consultants need to understand distributions. This article discusses how to understand different types of statistical distributions, understand the uses of different distributions, and make assumptions given a known distribution.
Knowing whether a process is in control and stable is paramount to producing a product or service that meets customer needs. In this hour-long Minitab training course, Eduardo Santiago covers many useful topics related to statistical process control.