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University of Colorado Boulder

Defining, Describing, and Visualizing Data

University of Colorado Boulder via Coursera

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Overview

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As leaders in your chosen field, you need to not only know how to ask the right questions but also answer them using data-based methods. Through this class, you will be able to get to the bottom of what you really want to know, describe the associated data related to that question, and visualize the information from that data to understand and explain the results. This course can be taken for academic credit as part of CU Boulder’s Master of Engineering in Engineering Management (ME-EM) degree offered on the Coursera platform. The ME-EM is designed to help engineers, scientists, and technical professionals move into leadership and management roles in the engineering and technical sectors. With performance-based admissions and no application process, the ME-EM is ideal for individuals with a broad range of undergraduate education and/or professional experience. Learn more about the ME-EM program at https://www.coursera.org/degrees/me-engineering-management-boulder.

Syllabus

  • Data and Measurement
    • Upon completion of this module, students will be able to classify types of data using measurement scales.
  • Working with Data in RStudio and ROIStat
    • Upon completion of this module, students will be able to work with datasets in RStudio and ROIStat.
  • Describing and Visualizing Data
    • Upon completion of this module, students will be able to use RStudio and ROIStat to calculate descriptive statistics to describe location, spread, and shape of data and create visual representations of data.
  • Determining Probabilities
    • Upon completion of this module, students will be able to apply the rules and conditions of probability to make decisions and solve problems.
  • Making Decisions with Discrete and Continuous Probability Distributions
    • Upon completion of this module, students will be able to apply both discrete and continuous probability distributions to make decisions and solve problems using RStudio and ROIStat.

Taught by

Wendy Martin

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