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Statistical data analysis, experimental design and scientific communication, studied in the context of experiments spanning a range of physical systems. Prerequisite: PHYS 133 or PHYS 141 or ENSC 120, with a minimum grade of C-. Recommended Prerequisite: CMPT 120. Quantitative.

Experiments investigating a range of physical phenomena such as Brownian motion, molecular order, chaotic dynamics, Doppler broadening of stellar spectra, and biophysical forces using techniques such as interference, optical trapping, and spectroscopy. Attention will also be given to more general skills, including experimental design, operating and troubleshooting experimental equipment, modeling of experimental results, data analysis, and the presentation of experimental results. Biological Physics students will do a selected set of experiments. Prerequisite: PHYS 233; PHYS 285 or CHEM 260; both with a minimum grade of C-. Writing/Quantitative.

Introduction to modern tools and methods for data acquisition, management, and visualization capable of scaling to Big Data. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, or ECON 233, and one of CMPT 102, CMPT 120, CMPT 125, CMPT 128, CMPT 129, CMPT 130, all with a minimum grade of C- or permission of the instructor. STAT 260 is also recommended. Quantitative.

Basic laws of probability, sample distributions. Introduction to statistical inference and applications. Prerequisite: or Corequisite: MATH 152 or 155 or 158, with a minimum grade of C-. Students wishing an intuitive appreciation of a broad range of statistical strategies may wish to take STAT 100 first. Quantitative.

The standard techniques of multiple regression analysis, analysis of variance, and analysis of covariance, and their role in observational and experimental studies. This course may not be used to satisfy the upper division requirements of the following programs: statistics major, statistics honours, actuarial science major, and actuarial science honours. Prerequisite: One of STAT 201, STAT 203, STAT 205, STAT 270, BUS 232, or ECON 233, with a minimum grade of C-. Students who have taken STAT 350 first may not then take the course for further credit. Quantitative.

An introduction to the essential modern supervised and unsupervised statistical learning methods. Topics include review of linear regression, classification, statistical error measurement, flexible regression and classification methods, clustering and dimension reduction. Prerequisite: STAT 260 and one of STAT 302 or STAT 305 or STAT 350 or ECON 333 or equivalent, with a minimum grade of C-. Quantitative.

Introduction to modern techniques in experimental physics, including computer-aided data acquisition, electronics, control theory, and statistical data analysis. Prerequisite: PHYS 233 and PHYS 255, both with a minimum grade of C-. Students with credit for PHYS 231 may not take this course for further credit. Quantitative.

Hands-on introduction to observational astronomy including the astrophysics of stellar clusters, galaxies, nebulae, and the expanding universe; calculation of the conditions for observing target objects; and analysis of photometric and spectroscopic data with Python. Data will be acquired using the Trottier Observatory, weather permitting, otherwise, archival data will be used. Prerequisite: PHYS 233 or equivalent, with a minimum grade of C-. Recommended Prerequisite: CMPT 120 or equivalent.

Computer-based approaches to solving complex physical problems. Includes topics such as Monte-Carlo and molecular dynamics techniques applied to thermal properties of materials; dynamical behavior of systems, including chaotic motion; methods for ground state determination and optimization, including Newton-Raphson, simulated annealing, neural nets, and genetic algorithms: symplectic methods; and analysis of numerical data. Prerequisite: MATH 260 or MATH 310; PHYS 255 or ENSC 380; CMPT 120 or equivalent. All prerequisite courses require a minimum grade of C-. Quantitative.

Includes topics such as qubits, density matrices, mixed states, entanglement, basic quantum algorithms, quantum cryptography, computational models and complexity, introductory quantum error correction, and applications. Prerequisite: PHYS 385; PHYS 384 or both MATH 314 and MATH 419, or equivalent. All prerequisite courses require a minimum grade of C-. Quantitative.

Postulates of statistical mechanics, partition functions, applications to gases, paramagnetism and equilibrium. Quantum statistics and applications. Prerequisite: PHYS 344 or CHEM 360, with a minimum grade of C-. Recommended: PHYS 385. Quantitative.