# Six Sigma Exploratory Data Analysis

Six Sigma Green Belt    |    Intermediate
• 13 videos | 37m 1s
• Includes Assessment
• CPE
In the Analyze stage of the Six Sigma DMAIC process, project teams carefully analyze process output and input variables. The goal of this data analysis is to narrow down the many possible inputs identified during the Measure stage, and lead to business process improvement. The analysis is carried out using tools that help identify a few probable issues and drive process improvement, process design, and process control. In this course, you'll learn about some of the key tools used in exploratory data analysis in Lean and Lean Six Sigma, such as Multi-varied studies, Correlation analysis, and Regression models. The course is aligned with ASQ's 2015 Six Sigma Green Belt Body of Knowledge.

## WHAT YOU WILL LEARN

• Identify characteristics of a multi-vari analysis Identify guidelines for creating sampling plans Distinguish between types of variation Interpret variation results in a given scenario Identify uses of correlation analysis in six sigma Make inferences about data based on a given scatter diagram
• Recognize considerations for interpreting the correlation coefficient Identify characteristics of causation Identify purpose of determining the statistical significance of a correlation coefficient Recognize how linear regression is used during data analysis Recognize appropriate conditions for hypothesis testing Calculate an outcome using the simple least-squares linear regression formula

## IN THIS COURSE

• Learn how to identify characteristics of a multivariate analysis.
• 3.  Sampling Plans for Multi-vari Analysis
In this video, you will learn how to identify guidelines for creating a sampling plan.
• 4.  Types of Variation
During this video, you will learn how to distinguish between types of variation.
• 5.  Interpreting Variation Results
Discover how to interpret variation results in a given scenario.
• 6.  Correlation Analysis
In this video, you will learn how to identify uses of correlation analysis in Six Sigma.
• 7.  Using Scatter Diagrams for Correlation Analysis
During this video, you will learn how to make inferences about data based on a given scatter plot.
• 8.  Correlation Coefficient
In this video, find out how to recognize considerations for interpreting the correlation coefficient.
• 9.  Causation
Learn how to identify characteristics of causation.
• 10.  Testing Statistical Significance
In this video, you will learn how to identify the purpose of determining the statistical significance of a correlation coefficient.
• 11.  Using Linear Regression
During this video, you will discover how to recognize how linear regression is used during data analysis.
• 12.  Hypothesis Testing for Regression Statistics
Discover how to recognize appropriate conditions for hypothesis testing.
• 13.  Using Regression Analysis to Predict Outcomes
In this video, you will learn how to calculate an outcome using the simple linear regression formula.

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