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Minitab 15 contains the tools and guidance to satisfy the most rigorous quality improvement projects
Minitab includes the full range of basic statistical procedures used for simple estimation and hypothesis testing with one or two samples. Among them are descriptive statistics and graphics, hypothesis tests and confidence intervals, variance, and association. Visit http://minitab.com/products/minitab/
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Choosing A Test: Two Proportion Or Two Sample T-Test?
This article includes a description of whether one should use a 2 proportion test, or a 2 sample t-test when analyzing data. From the iSixSigma Discussion Forum.
Concept, Model and Application
General principles of the hypothesis test. From Southwest Missouri State University.
Errors in Hypothesis Testing
Can't remember which type is a worse mistake to make? Here's an overview. From Southwest Missouri State University.
How to Compare Data Sets - ANOVA
An ANOVA is a guide for determining whether or not an event was most likely due to the random chance of natural variation. Or, conversely, the same method provides guidance in saying with a 95% level of confidence that a certain factor (X) or factors (X, Y, and/or Z) were the more likely reason for the event. From Daniel Sloan and iSixSigma.
Logic of Hypothesis Testing
Ruling out chance, the null hypothesis, steps to test, type I and II errors, one and two-tailed tests, confidence intervals and findings. From David Lane and Rice University.
P Values and Statistical Significance
Remembering the statistical significance of the P Value is always tough. Learn from your peers and use this simple saying to remember the significance of P Values forever. From iSixSigma.
Type I and Type II Errors - Making Mistakes in the Justice System
Ever wonder how someone in America can be arrested if they really are presumed innocent, why a defendant is found not guilty instead of innocent, or why Americans put up with a justice system which sometimes allows criminals to go free on technicalities? These questions can be understood by understanding the similarity of the American justice system to hypothesis testing in statistics and the two types of errors it can produce. From Intuitor.
When Definitions Collide
Think before you act when viewing an observed difference with your hypothesis test -- it could be important but not significant. From Quality Digest, written by Thomas Pyzdek.
Why P Value of < 0.05 To Say Data Is Normal?
Why should the P-value be greater than 0.05 to conclude that the available data set is normal? What does the 0.05 signify? These questions and more are answered in this discussion forum thread From iSixSigma.
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