Denver, CO 9/6/2007 8:45:00 PM
News / Business

Announcing Normality Tests for Microsoft Excel

KnowWare International Inc. announces the addition of a normality test to the QI Macros SPC (statistical process control) software for Excel. Some statistical methods assume that the data is normal (i.e., bell-shaped). If it’s non-normal (e.g., skewed left, right, exponential, or other distribution), assuming data is normal can lead to erroneous conclusions. What users want to know is:

    · Is my data normal?

To answer this question, the normality test in the QI Macros SPC Software for Excel delivers not one, but four ways to assess normality: a normal probability plot, histogram, Anderson-Darling p and critical values that enable users to quickly determine if their data is normal or non-normal. To find out more about normality tests go to http://www.qimacros.com/excel-tips/normality-test.html.


The QI Macros are an add-in for Microsoft Excel that automate all of the charts and diagrams required for statistical process control (SPC) and Lean Six Sigma. There are over 75,000 registered users. The QI Macros consist of four parts:

   1. 21 Macros that use existing Excel data to create pareto, control charts, and histograms.

   2. Over 60 fill-in-the-blank templates for Lean Six Sigma and ISO documentation.

   3. Statistical analysis tools like ANOVA, f-test, regression, and a sample size calculator.

   4. Data transformation tools like restacking, word counts and cross tabulation.

Unlike complex statistical tools, the QI Macros tools can be used by anyone from nurses to Six Sigma Black Belts. Users most often say that the QI Macros are convenient and hassle free:

    · Easy to learn. The pull-down menu gives immediate access to all tools.

    · Works directly on Excel data.

    · Automates the most commonly used Lean Six Sigma improvement tools.

30-day evaluation copies of the QI Macros for Excel can be downloaded at www.qimacros.com/freestuff.html. Readers can also signup for a free email course on Lean Six Sigma.