Six Sigma Black Belt: Using Basic Statistics and Graphical Methods

  • 8 Videos | 1h 48m 41s
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Organizations must ensure that their products and services are extremely consistent to desired specifications, as variations can lead to rejected orders, reworks, and eventually, customer dissatisfaction and financial losses. Statistics can provide Black Belts with the tools to summarize and assess collected data in a meaningful way for identifying sources of variation and controlling them. Black Belts can use descriptive (enumerative) statistics to tabulate and graphically represent sample data through a number of informative charts and diagrams. Using analytical (inferential) statistics, supported by the central limit theorem, Black Belts can confidently make inferences, test the statistical validity of their inferences, and optimize and control processes. This course provides Black Belts with basic statistical tools for describing, presenting, and analyzing data. It explores the process of preparing and presenting sample data using graphical methods and then making valid inferences about the population represented by the sample. This course is aligned with the ASQ Certified Six Sigma Black Belt certification exam and is designed to assist learners as part of their exam preparation. It builds on foundational knowledge that is taught in SkillSoft's ASQ-aligned Green Belt curriculum.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    calculate measures of dispersion in a given scenario
    match measures of central tendency to their characteristic advantages and limitations
    construct a cumulative frequency diagram in a given scenario
    recognize how to set class intervals for frequency distributions
    predict and interpret the histogram shape that would result from a given frequency distribution
    recognize how to use normal probability plots to determine whether data is normally distributed
  • identify statements that reflect correct interpretations of a complex box plot
    identify the best interpretation of a given run chart
    recognize how to use a scatter plot to find the optimum target value and tolerance zones for a process parameter
    recognize the significance of central limit theorem in the application of hypothesis tests
    recognize the significance of the central limit theorem for inferential statistics
    match tools for drawing valid statistical conclusions to descriptions of their use

IN THIS COURSE

  • Playable
    1. 
    Six Sigma Black Belt: Using Basic Statistics and Graphical Methods
    1m 59s
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  • Playable
    2. 
    Types of Descriptive Statistics
    15m 51s
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    3. 
    Frequency Distributions and Cumulative Frequency
    9m 24s
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    4. 
    Histograms and Probability Plots
    13m 29s
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    5. 
    Bar Charts, Box Plots, and Run Charts
    12m 28s
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    6. 
    Scatter Diagrams and Process Parameters
    8m 46s
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    7. 
    Statistics and the Central Limit Theorem
    11m 23s
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    8. 
    Tools for Reaching Valid Statistical Conclusions
    11m 22s

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