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Overview/Description
"Measure what is measurable, and make measurable what is not so" said Galileo Galilei, the famous Italian physicist, mathematician, astronomer, and philosopher. Measuring the key characteristics in your current processes is a very significant step in any Six Sigma improvement journey. As such, sample data from existing processes needs to be identified, collected, presented, and analyzed. Collecting data that is correct and useful is one of the first steps in the measurement process. Various types of data exist, and they all need appropriate treatment during the collection...
Overview/Description
Businesses exist to meet the needs of the customers they serve. As such, you must listen to the voice of your customers and build processes that deliver products and services to them. It is also necessary to review processes to ensure they remain within the targets and specifications set by your customers. Measuring the capability and performance of a process is an important activity in Six Sigma DMAIC methodology. Six Sigma teams use process capability and performance measurements, such as process capability (Cp), process capability index (Cpk), process performance (Pp...
Overview/Description
"If you can't describe what you are doing as a process, you don't know what you are doing," says W. Edwards Deming, a well-known American quality advocate, statistician, and educator. During the Measure stage of the Six Sigma methodology, you need to identify and map processes and procedures for problem areas identified during the Define stage, and present them to the Six Sigma team for a closer look. As you start uncovering and analyzing these processes, the likely causes of problems become clearer. This course will examine the tools and techniques used to model and...
Overview/Description
Probability distributions are an essential part of descriptive statistics that Six Sigma teams can use to assist in fitting collected data into various types of distributions. Probability distributions help to ascertain specific probability values in the distribution and lead the Six Sigma teams down the hypothesis testing roadmap to the next stage of the Six Sigma DMAIC process. Of course, all this is meaningless if the data you have gathered and used is not accurate or precise, which is where measurement systems analysis (MSA) comes into play. MSA is a task in the...
Overview/Description
Six Sigma bases its analysis and findings on the facts and figures at hand. Statistical studies and probability are the key tools that Six Sigma teams use to measure and analyze issues that are identified in the early stages of Six Sigma projects. 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...
Overview/Description
Six Sigma teams use measures of central tendency and dispersion to reveal key facts about process data and the existing processes. They summarize data and put forth the relationships between various data components for further analysis. The teams then present these relationships in easy-to-understand graphical forms that facilitate comparison and help to identify possible trends. This course deals with the basic concepts of descriptive statistics, such as measures of central tendency and dispersion, and their significance in Six Sigma data analysis. The course also shows...
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