PH 264 Introduction to Physical Data Analysis
Emphasizes project-driven hands-on experience in computational physics and data analysis. Includes the use of basic computational skills in accessing and manipulating arrays of data, plotting relationships and using statistical libraries. Teaches quantitative methods to characterize standard systems studied in physics and streams of data. Interprets data based on underlying physics models and outcomes of statistical inference; communicates conclusions and uncertainties of observations.
Prerequisite
MTH 251Z Differential Calculus with a grade of C or better (may be taken concurrently).
Notes
Lower Division Transfer (LDT) Course
General Education Requirements
AAOT Science/Math/CS Non Lab, AGS Math/Science
Outcomes
Upon successful completion of this course, students will be able to:
Read VPython code and describe the underlying physics concept that has been implied for writing the program. Simulate motion by creating a VPython program including the representation of position, velocity and acceleration vectors on the screen. Write a VPython program as a solution to a Newton's mechanics physics problem and visualize on the computer screen common physical properties. Solve problems containing Newton's mechanics that include the effects of friction and drag forces.