Taking samples of information can be an efficient way to draw conclusions when the cost of gathering all the data is impractical. Sound conclusions can often be drawn from a relatively small amount of data.
Help Green Belts use statistical analysis by emphasizing not only when and why a tool or methodology is used but also what the data says in "plain English." Memorizing complex formulas is not necessary, but basic formulas, should be shared.
Learn how to determine the sample size necessary for correctly representing your population.
Learn how to randomly sample your population to ensure no bias.
Most surveys draw their conclusions from a sampling a larger group. How well the sample represents the larger population is gauged by two important statistics which quality professionals should understand – the margin of error and confidence level.
By following a consistent reporting format, a Six Sigma team and its customers can better understand and explain hypothesis test results and conclusions.
In sampling, a comparatively small number of customers, called a sample, is used to draw conclusions about a population. Although this method saves time and money, it comes with a higher margin of error that must be taken into consideration.
The stratification process starts with a broad population and breaks it into manageable segments. Quickly done up front with some basic statistics, it can be used to identify, quantify, isolate and manage the routine and the noise in processes.