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FUNDAMENTALS OF MINITAB

Course Description: Decrease the time required for statistical analysis by quickly learning to navigate Minitab's user-friendly and customizable environment. Learn how to import/ export data and output between MINITABtm and various software and database systems

Enhance your ability to create, manipulate, and restructure data. Develop sound statistical approaches to data analysis by learning how to create and interpret a wide variety of graphs and numerical measures useful for quality improvement initiatives. This course focuses on the utilization of these tools as they pertain to applications commonly found in manufacturing, engineering, and business processes.
 

TARGET AUDIENCE   COURSE LENGTH AND COST
Anyone who uses MINITABtm to perform data analysis, including Quality Professionals, Engineers, Scientists, Managers, Analysts, and Instructors can benefit from this course. Length: 2 days
Time: 8:00 a.m. - 4:00 p.m.
One-hour lunch break is on your own

Please see our public training schedule for prices, dates and locations.

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WHAT’S COVERED

topics covered

I.       Introductions
            Current Minitab use
            Specific tools preferred

II.      Basic Statistics Review

III.     MINITABtm Basics
            Structure
            Menus
            Help
            StatGuide

IV.     Histograms
            Normal Distribution
                Splitting Worksheets
                Normality Testing
            Non-normal Distribution
                Editing Graphs

V.      Capability Studies Part One - Normal Distribution

VI.      Capability Studies Part Two - Non-normal Distribution
            Box-Cox Transformation
            Fitted Distribution

VII.    SPC Charts
            X Bar and R Charts
            P Charts

VIII.    Comparing Data Sets/Hypothesis Testing
             Boxplots
             ANOVA
             Correlation
             Regression Analysis

IX.       Sample Size

X.        Gage R&R
               Bias Study
               X Bar & R
               ANOVA

XI.       Designed Experiments


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