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What you'll learn

Explain why probability is important to statistics and data science.

See the relationship between conditional and independent events in a statistical experiment.

Calculate the expectation and variance of several random variables and develop some intuition.

Skills you'll gain

Statistical Inference

Data Science

Probability Distribution

Statistics

Bayesian Statistics

Statistical Analysis

Probability

Probability & Statistics

There are 7 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 Logo adapted from photo by Christopher Burns on Unsplash.

Descriptive Statistics and the Axioms of Probability

Conditional Probability

Discrete Random Variables

Continuous Random Variables

Joint Distributions and Covariance

The Central Limit Theorem