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Phys 114 - Introduction to Data Reduction with Applications (3-0-3)
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, is discussed. The course enables students to apply the concepts of data reduction and error analysis using data analysis software applied to real data sets found in the physical sciences.
COURSE OUTLINE (including lecture notes and HW assignments)
WEBEX recording Lecture 01, Lecture 02
Research for Students and Lecture 03 part A, Lecture 03 Part B, Lecture 03 Part C and Lecture 04
Need help with Matlab?
Go to the MATLAB webpage: https://www.mathworks.com/ and look for "learning Matlab" or search for HELP videos
Math department help (they also use MATLAB):
http://math.njit.edu/students/undergraduate/matlab.php
http://math.njit.edu/students/undergraduate/matlab_ta_hours.php
GRADES and Logbook of Assignments: SECTION 001
Home work Solutions: Goto HW solutions page
Exam and Quiz Solutions, Equation Sheet : Solutions page
Review for EXAM 2: Exam 2 from 2022 part A, Exam 2 from 2022 part B
Review for Final Exam - Webex recordings
From 2022 - Part A, Part B
From 2021 - Part A , Part B
PLEASE NOTE THAT THE COURSE CONTENT VARIES FROM YEAR TO YEAR. Consult the syllabus and assigned HW problems and labs to determine what will be covered on this year's exams
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