Population Archive

Basic Sampling Strategies: Sample vs. Population Data

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.

Eliminating the Fear About Using Confidence Intervals

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.

How to Determine Sample Size, Determining Sample Size

Learn how to determine the sample size necessary for correctly representing your population.

Is There Bias In Your Random Sample?

Learn how to randomly sample your population to ensure no bias.

Margin of Error and Confidence Levels Made Simple

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.

Reporting Format for Hypothesis Testing

By following a consistent reporting format, a Six Sigma team and its customers can better understand and explain hypothesis test results and conclusions.

Sample Correctly to Measure True Improvement Levels

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.

Stratification Leads to Specialized Improvements

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.

Posts Tagged ‘population’