Statistical analysis made easy
There was a time when performing statistical analysis of data was laborious and required a talent for mathematics. With the prevalence of spreadsheet programs, such as Microsoft Excelâ data analysis has become simple and routine. Therefore, nearly anyone who can point a mouse can utilize the power of statistical methods for quality improvement.
Having knowledge of easy-to-use statistical tools to understand variation quantitatively and act to reduce it is a powerful advantage. All too often, decisions are made based more on opinion than fact, and our processes remain more of an art than a science. This training will enable participants with basic statistical skills to become adept with the Data Analysis, Charting,
and Function Wizard
aspects of Excel. The techniques taught are fundamental methods for Six Sigma Quality Improvement Programs.
Who should attend this seminar?
Managers, supervisors, and engineers in manufacturing companies. It is particularly well suited for design, manufacturing and quality engineers. All participants should have a basic understanding of statistics and the use of Microsoftâ Excel. This class is required for those taking the Six Sigma Green Belt series certificate. (Save 20% if you register for the certificate. Call 952.358.8343 to gain discount.)
On completion of this seminar,
You will be able to:
- Use statistical methods to acquire data, analyze it and make it meaningful, present it clearly and enable better decisions.
- Design tests and experiments for successful results.
- Analyze data you bring with you from your own work.
- Achieve process and design improvements through the use of statistical methods.
- Utilize methods using exercises with Excel® worksheets free to take with you.
- Utilize these techniques for Six Sigma Quality Improvement Programs.
It includes a certificate of completion and requires eight hours of class time. All materials are provided, including sample Microsoft Excel data files and worksheets for the techniques.
- Descriptive statistics
- Histograms and other charting methods
- Process capability studies (Cpk)
- Correlation and regression analysis
- Hypothesis testing (tests of significance) t-test,f-test, z-test, ANOVA
- Exponential smoothing
- Randomization and sampling