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Wendy Martin

Data analysis skills are widely sought by employers, both nationally and internationally. This specialization is ideal for anyone interested in data analysis for improving quality and processes in business and industry. The skills taught in this specialization have been used extensively to improve business performance, quality, and reliability.

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Data analysis skills are widely sought by employers, both nationally and internationally. This specialization is ideal for anyone interested in data analysis for improving quality and processes in business and industry. The skills taught in this specialization have been used extensively to improve business performance, quality, and reliability.

By completing this specialization, you will improve your ability to analyze data and interpret results as well as gain new skills, such as using RStudio and RMarkdown. Whether you are looking for a job in data analytics, operations, or just want to be able to do more with data, this specialization is a great way to get started in the field.

Learners are encouraged to complete this specialization in the order the courses are presented.

This specialization can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

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What's inside

Three courses

Managing, Describing, and Analyzing Data

In this course, you'll learn the fundamentals of data management, description, and analysis. You'll master data classification, graphical and numerical data description, and probability distributions. You'll also explore sampling error, sampling distributions, and decision-making errors.

Stability and Capability in Quality Improvement

In this course, you will learn to analyze data for stability and statistical control using R software. You will also learn how to assess a process's capability of meeting specifications and make decisions about process improvement.

Measurement Systems Analysis

In this course, you will analyze measurement systems for process stability and capability. You will analyze continuous measurement systems and statistically characterize both accuracy and precision using R software. You will perform measurement systems analysis for potential, short-term and long-term statistical control and capability.

Learning objectives

  • Manage, describe, and analyze data using applied statistics
  • Apply continuous and/or discrete data methods for process analysis, improvement, and ongoing management in a business or workplace
  • Analyze measurement systems to ensure their stability and capability

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