In this course, you will learn to analyze data in terms of process stability and statistical control and why having a stable process is imperative prior to perform statistical hypothesis testing. You will create statistical process control charts for both continuous and discrete data using R software. You will analyze data sets for statistical control using control rules based on probability. Additionally, you will learn how to assess a process with respect to how capable it is of meeting specifications, either internal or external, and make decisions about process improvement.

About this Course
Background knowledge in statistics is helpful; visit Managing, Describing, and Analyzing Data as a prerequisite to this course. R / RStudio required.
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Try Coursera for BusinessWhat you will learn
Understand how to use, select, and interpret process control charts to identify special causes of variation
Create and interpret control charts for normal and non-normal distributions
Create and interpret control charts for discrete data
Analyze the capability of a process to meet customer specifications
Skills you will gain
- Analyzing a process for capability
- Analyzing a process for stability
- Make decisions about process improvement
- R Programming
- Rstudio
Background knowledge in statistics is helpful; visit Managing, Describing, and Analyzing Data as a prerequisite to this course. R / RStudio required.
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Try Coursera for BusinessOffered by
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Syllabus - What you will learn from this course
Understanding Process Variation, Process Control and Control Charts
Xbar and R / Xbar and S Charts / X and MR Charts
X and Moving Range Charts for Non-Normally Distributed Data
Process Capability
About the Data Science Methods for Quality Improvement Specialization

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