March 23, 2022

Exploratory Data Analysis

Before any problem can be eliminated or controlled, the cause of the problem must be identified and confirmed. Six Sigma teams use statistical tools to perform an analysis of data to identify and confirm the variable that causes most variation in a process or product. By the end of this course, you will be able to • Create and interpret multi-vari studies • Identify the differences between positional, cyclical, and temporal variations • Identify the largest source of variation in a process using a multi-vari study • Interpret the linear correlation coefficient • Determine the statistical significance of a linear correlation coefficient • Identify the equation for linear regression
March 23, 2022

Hypotheses Test Basics

Hypotheses tests are statistical methods of making decisions on the results of a study to determine if the results are truly related, or if they occur by chance. Hypotheses tests differ in the results they produce and what information is required, but they all share some basic terms and concepts. By the end of this course, you will be able to • Define and distinguish between statistical significance and practical significance • Apply tests for significance level, power, and type I and type II errors • Define null and alternative hypotheses • List acceptable null and alternative hypotheses for statistical parameters • Determine appropriate sample size for various tests • Define confidence levels and confidence intervals • Calculate confidence intervals for population parameters
March 23, 2022

Hypotheses Tests

Six Sigma teams must understand the difference between the types of hypotheses tests to determine the proper test for the problem. Selection of the proper test is determined by the statistical parameter to be tested and the available information from the sample data. By the end of this course, you will be able to • List common hypotheses tests • Define and describe paired-comparison hypotheses tests • Define terms related to one-way ANOVAs and interpret their results and data plots • Define and interpret chi-square and use it to determine statistical significance
March 23, 2022

Design of Experiments

Properly designed experiments are essential to improving a Six Sigma project and making the project successful. By the end of this course, you will be able to • Define terms associated with the design of experiments • Interpret main effects of a factor • Interpret interaction plots
March 23, 2022

SPC

Statistical Process Control, or SPC, is a quality control methodology that uses statistics to predict variation in processes. SPC is the basis for the control portion of a Six Sigma project. By the end of this course, you will be able to • Define statistical process control • Define and describe the objectives and benefits of statistical process control • Explain the types of variation that exist in a process • Define and describe how rational subgrouping is used • Identify, select, construct, and apply various control charts • Interpret various control charts
March 23, 2022

Implement and Validate

Improvements to a process are almost always needed to meet the goals of an organization. Many Six Sigma tools can be used to implement and validate the improvements. By the end of this course, you will be able to • List the steps to improve a process • Identify Six Sigma tools used to improve a project • Identify Six Sigma tools used to validate improvement efforts
March 23, 2022

Control Plans

The control plan is one of the most important documents used to maintain the gains made during the analysis and improve portions of a Six Sigma project. The control plan is a “living” document that is continually updated to capture continuing improvements. By the end of this course, you will be able to • Define the minimum requirements for a control plan • List sources of information for a control plan • List required documents based on a control plan • Define a dynamic control plan
March 23, 2022

Probability and Statistics

In today’s business world, companies cannot remain competitive if they must measure every product’s weight, color, size, strength, and any other characteristic 100 percent. Organizations use probability and statistics to measure samples of a product and provide mathematical proof of the quality of the product or process. By the end of this course, you will be able to • Define probability • Describe and apply probability concepts • Define statistics • List statistical parameters • Distinguish between descriptive and inferential statistics • Distinguish between a population parameter and a sample statistic • Define a central limit theorem and its significance in statistics
March 23, 2022

Collecting and Summarizing Data

To improve a process or product it is important to know its current status and its status after improvements are made. Valid data must be collected and summarized to verify the status of the process or product. By the end of this course, you will be able to • Identify continuous or variable data • Identify discrete or attribute data • Describe and define nominal, ordinal, interval, and ratio measurement scales • Define and apply methods for collecting data • Define and apply techniques such as random sampling, stratified sampling, and sample homogeneity • Depict relationships by constructing, applying, and interpreting diagrams and charts