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Six Sigma Training Video | Six Sigma Green Belt Tutorial | Measure Phase Explained

Introduction to Measure Phase: The Measure phase is the second phase in a six sigma project. The key objective of the measure phase is to gather as much information as possible on the current processes. This involves three key tasks, i.e. (pronounced as “that is”), creating a detailed process map, gathering baseline data, and summarizing and analyzing the data.
Process Modeling: Process modeling refers to the visualization of a proposed system, layout, or other change in the process. Process modeling and simulation can determine the effectiveness or ineffectiveness of a new design or process. They can be done using process mapping and flow charts.

Watch the full video to know more about the following topics:
Process Mapping, The given flowchart shows the processes involved in Software development, Work Instructions, Process Input and Output Variables, Probability and Statistics, Probability, Basic Properties of Probability, Probability—Common Terms and Example, Probability Concepts, Multiplication Rules or AND Rules, Permutation and Combination, Calculating Permutation and Combination—Example, Types of Statistics, Analytical Statistics, Types of Errors, Central Limit Theorem, Central Limit Theorem—Graph, Central Limit Theorem—Conclusions, Statistical Distributions, Discrete Probability Distribution, Binomial Distribution, Calculating Binomial Distribution—Example, Poisson Distribution, Poisson Distribution—Formula, Calculating Poisson Distribution—Example, Normal Distribution, Calculating Normal Distribution—Example, Z-Table Usage, Z-Table, Chi-Square Distribution, Chi-Square Distribution—Formula, F-Distribution, Collecting and Summarizing Data, Types of Data, Selecting Data Type, Measurement Scales, Assuring Data Accuracy, Simple Random Sampling vs. Stratified Sampling, Data Collection Methods — Check Sheets, Data Coding, Descriptive Statistics—Measures of Central Tendency, Mean, Median, and Mode — Example, Mean, Median, and Mode — Outliers, Descriptive Statistics — Measures of Dispersion, Measures of Dispersion — Range, Measures of Dispersion — Variance, Measures of Dispersion — Standard Deviation, Descriptive statistics — Frequency Distribution, Cumulative Frequency Distribution, Graphical Methods – Stem and Leaf Plots, Graphical Methods — Box and Whisker Plots, Graphical Methods—Scatter Diagrams, Scatter Diagram—Types of correlation, Graphical Methods—Histogram, Graphical Methods — Normal Probability Plots, Measurement System Analysis, Measurement System Analysis, Measurement System Analysis—Objectives, Measurement Analysis, Types of Measurement Errors, Sources of Variation, Gage Repeatability and Reproducibility, Components of GRR Study, Guidelines for GRR Studies, Other GRR Concepts, Measurement Resolution, Repeatability and Reproducibility,, Data Collection in GRR, ANOVA Method of Analyzing GRR Studies, Interpretation of Measurement System Analysis, Gage RR Template, Gage RR Results Summary, Gage RR Interpretation, Process and Performance Capability, Natural Process Limits vs. Specification Limits, Process Performance Metrics, Calculating Process Performance — Example, Process Stability Studies, Process Stability Studies—Run Charts in Minitab, Process Stability Studies – Causes of Variation, Verifying Process Stability and Normality, Process Capability Studies, Objectives of Process Capability Studies, Identifying Characteristics, Identifying Specifications or Tolerances, Process Performance Indices, Key Terms in Process Capability, Short Term and Long Term Process Capability , Assumptions and Conventions — Process Variations, Stability, Capability, Spread, and Defects Summary, Comparing Cpk and Cp, Process Variation — Example, Effect of Mean Shift, Process Capability for Attribute Data — Key Concepts, Quiz.

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