Introduction to Data Reduction with Applications

Corequisite: MATH 111. Physics majors only. An introduction to both the theory and application of error analysis and data reduction methodology. Topics include the binomial distribution and its simplification to Gaussian and Poisson probability distribution functions, estimation of moments, and propagation of uncertainty. Forward modeling, including least-squares fitting of linear and polynomial functions are discussed. The course enables students to apply the concepts of the data reduction and error analysis using data analysis software to real data sets found in the physical sciences.

Term 202410 #14860 PHYS114
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Instructor
Gerrard, Andrew J. Email View Faculty Courses
Meeting Times
Location: TIER 105 (NK)
@ 13:00 - 14:20
From 2024-01-16 to 2024-05-09
Enrollment

20

seats available

19

currently enrolled

39

maximum enrollment

99

waitlist seats available

99

waitlist capacity

Section Tally

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