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This bundle includes: "Modeling and Analyzing Processes in Six Sigma - 2.0 hours/PDUs" Item No.oper_07_a01_bs_enus"Statistics and Probability in Six Sigma - 2.0 hours/PDUs" Item No.oper_07_a02_bs_enus "Data Classification and Collection in Six Sigma - 1.5 hours/PDUs" Item No.oper_07_a03_bs_enus "Summarizing and Presenting Data in Six Sigma - 1.5 hours/PDUss" Item No.oper_07_a04_bs_enus "Probability Distributions and Measurement Systems Analysis in Six |
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This course will explore continuous and discrete types of data, and nominal, ordinal, interval, and ratio measurement scales. It will also introduce methods for data collection, such as check sheets and coded data, and deals with the issue of data accuracy and integrity, focusing particularly on sampling techniques such as random sampling and stratified sampling. The course is aligned to the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their |
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This course will examine the key concepts of process capability and performance, and the methods of measuring and interpreting them in a process capability study. It covers the calculation and interpretation of process capability and performance measurements. It also identifies key considerations for measuring process capability, such as short-term and long-term capability and process capability for discrete data. |
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This course will examine the tools and techniques used to model and analyze existing processes. From a process modeling perspective, the course looks at techniques such as process mapping, written procedures, and work instructions. From a process analysis point of view, the course examines the use of SIPOC analysis to identify process input and output variables, and explores how cause-and-effect diagrams and relational matrices are used to establish relationships between problems and potential c |
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This course will examine how to calculate normal, binomial, Poisson, chi-square, Student's t-distributions, and F distributions. It will also look at how to assess the precision and accuracy of an organization's current measurement system using Gauge Repeatability and Reproducibility (GR&R), bias, linearity, percent agreement, and Precision/tolerance (P/T) studies. |
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This course explores basic statistical concepts that apply to Six Sigma. It distinguishes between enumerative and analytical statistics and population and sample characteristics, and describes the Central Limit Theorem. It also examines basic probability concepts and looks at dependent, independent, and mutually exclusive events, and multiplication and addition rules. |
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The course also shows how to apply graphical methods, such as stem-and-leaf plots, box-and-whisker plots, run charts, and scatter diagrams, for illustrating relationships among various components of a given dataset. In addition, it examines how to depict distributions using histogram and normal probability plots. |
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