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Course Description

Foundational treatment of probability theory with a focus on science and engineering applications. Elements of probability theory, random variables and their properties, probability distributions: discrete and continuous, conditional probability, joint distributions, derived distributions, laws of large numbers and reality of small numbers, properties of estimators, and estimation of confidence intervals. Emphasis on analysis and implications of small data, data from skewed and fat-tail distributions commonly used in risk analysis and engineering decision making. Recommendation: Undergraduate Level Probability & Statistics and Coding Experience

Basic Enrollment Requirements: 

Academic Year (Fall/Spring): Unofficial Transcript – Bachelor’s + 3.0 GPA.

Summer: None.

Refund Policy:?The refund policy for Courses at Tufts offerings is dependent on the course length. Please refer to the section details to confirm any exceptions to the standard refund policy. The refund policies are viewable here:? 

Remission Eligible: Yes; first day of term; all university policies apply.

Affiliated With:

  • School of Engineering