ENGRD 2700 - Eng Probability and Statistics: Modeling and Data Science

(MQL-AG, OPHLS-AG)

Fall, Spring, Summer. 4 credits. Student option grading (no audit).

Forbidden Overlap: due to an overlap in content, students will receive credit for only one course in the following group: AEM 2100, BTRY 3010, BTRY 6010, CRP 1200, HADM 2010, HADM 2011, ILRST 2100, ILRST 6100, MATH 1710, PUBPOL 2100, PUBPOL 2101, PSYCH 2500, SOC 3010, STSCI 2100, STSCI 2200, STSCI 2150.
Prerequisite: MATH 1910, MATH 1920.

Fall: Y. Chen; Spring: J. Pender; Summer: Staff.

Gives students a working knowledge of basic probability and statistics and their application to engineering. Includes computer analysis of data and simulation. Topics include: random variables, probability distributions, expectation, estimation, testing, experimental design, quality control, and regression.

Outcome 1: Understand the breadth of decision situations with uncertainty that arise in engineering, industry, and society.

Outcome 2: Develop the skills needed for extracting information from data in real-world decision situations.

Outcome 3: Learn methods of probability modeling and data analysis.

Outcome 4: Build familiarity with current software used for statistical inference and data analysis.