In this issue:

• Recession Specials
• $90 Off on Any 2 Individual Courses till January 15, 2 Weeks Extra till December 24
• Planned Additions: Reworked Advanced Statistics, PDF Version of Glossary
• In Focus: Nonparametric Tests
• MiC Quality Online Courses
• Free Resources
• Next Update

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The downturn in the economy makes the advantages of online learning more compelling than ever. Companies can use e-learning to avoid the costs of travel and lost productivity. Employees can enhance their skill base to become more attractive to employers. Wise companies will also use some of spare capacity to improve their processes and become as efficient and competitive as they possibly can.

In order to help coping with the recession we have created a new special that allows to select any 2 of our courses and receive $90 off the combined individual prices. This is separate to our standard packages with discounts for both statistics, both SPC, or both DOE courses. So if you would like to take, for example, DOE and MSA courses, you will save $90. If you enroll before Christmas you can also take advantage of our second special - 2 weeks extra free of charge. See the relevant Promotional Codes below.

We are currently reworking our Advanced Statistics course. Many of the students who take this course work in scientific research or healthcare. We are adding more material on hypothesis testing and nonparametric tests, including more exercises and case studies. We will also divide the course into a number of separate modules so people can select the topics they need thus saving some money.

We will be releasing a PDF version of our Six Sigma and Quality Glossary (available online at: http://www.micquality.com/six_sigma_glossary/index.htm) in January. Apart from the electronic version we will be offering printed versions in standard and pocket sizes. We are also exploring options for publishing all our reference materials in a book form.

If you are interested in getting a copy of the Glossary or the complete Reference book please let us know. The cost will depend on the format and how much interest we will get.

Most types of hypothesis test require that the population conforms to a particular distribution, usually the normal distribution. Where this is not the case a nonparametric test can be used.

Nonparametric tests make no assumptions about the type of distribution (although they may require symmetry, or some other property). The disadvantage is that nonparametric tests are not as efficient; for a given data set the nonparametric test will give a higher p-value.

Nonparametric Tests include:

Parametric tests include ANOVA, the t test, the F test and the chi-square test.