Managing, Describing, and Analyzing Data

This course is part of Data Science Methods for Quality Improvement Specialization

Instructor: Wendy Martin

What you'll learn

  •   Calculate descriptive statistics and create graphical representations using R software
  •   Solve problems and make decisions using probability distributions
  •   Explore the basics of sampling and sampling distributions with respect to statistical inference
  •   Classify types of data with scales of measurement

    • Skills you'll gain

  •   Probability & Statistics
  •   Statistics
  •   Statistical Inference
  •   Sampling (Statistics)
  •   Probability
  •   Data Analysis
  •   Statistical Hypothesis Testing
  •   Statistical Analysis
  •   Data Literacy
  •   Histogram
  •   R Programming
  •   Descriptive Statistics
  •   Probability Distribution
  •   Statistical Visualization

    • There are 5 modules in this course

    This course 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.

    Describing Data Graphically and Numerically

    Probability and Probability Distributions

    Sampling Distributions, Error and Estimation

    Two Sample Hypothesis Testing

    Explore more from Probability and Statistics

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