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71 - 80 of 119 results for: all courses

GS 42N: Landscapes and Tectonics of the San Francisco Bay Area

Active faulting and erosion in the Bay Area, and its effects upon landscapes. Earth science concepts and skills through investigation of the valley, mountain, and coastal areas around Stanford. Faulting associated with the San Andreas Fault, coastal processes along the San Mateo coast, uplift of the mountains by plate tectonic processes, and landsliding in urban and mountainous areas. Field excursions; student projects.
Terms: Aut | Units: 4 | UG Reqs: WAY-AQR, WAY-SMA | Grading: Letter (ABCD/NP)

HUMBIO 85A: Essential Statistics for Human Biology (BIO 108)

Introduction to statistical concepts and methods that are essential to the study of questions in biology, environment, health and related areas. The course will teach and use the computer language R and Python (you learn both, choose one). Topics include distributions, probabilities, likelihood, linear models; illustrations will be based on recent research.
Terms: Spr | Units: 4 | UG Reqs: WAY-AQR | Grading: Letter (ABCD/NP)

HUMBIO 88: Introduction to Statistics for the Health Sciences

Students will learn the statistical tools used to describe and analyze data in the fields of medicine and epidemiology. This very applied course will rely on current research questions and publicly available data. Students will gain proficiency with Stata to do basic analyses of health-related data, including linear and logistic regression, and will become sophisticated consumers of health-related statistical results.
Terms: Win | Units: 4 | UG Reqs: GER:DB-Math, WAY-AQR | Grading: Letter (ABCD/NP)

HUMBIO 89: Statistics in the Health Sciences

This course aims to provide a firm grounding in the foundations of probability and statistics, with a focus on analyzing data from the health sciences. Students will learn how to read, interpret, and critically evaluate the statistics in medical and biological studies. The course also prepares students to be able to analyze their own data, guiding them on how to choose the correct statistical test, avoid common statistical pitfalls, and perform basic functions in R deducer.
Terms: Aut, Win | Units: 3 | UG Reqs: GER:DB-Math, WAY-AQR | Grading: Letter or Credit/No Credit

HUMBIO 154A: Disease control systems: epidemics, outbreaks, and modeling for public health (CHPR 254)

(HumBio students must enroll in HumBio 154A.)This course teaches operations research and modeling techniques to improve public health programs and disease control systems. Students will engage in in-depth interdisciplinary study of disease detection and control strategies from a "systems science" perspective, which involves the use of common mathematical modeling and operations research techniques such as optimization, queuing theory, Markov and Kermack-McKendrick models, and microsimulation. Lectures and problem sets will focus on applying these techniques to classical public health dilemmas such as how to optimize screening programs, reduce waiting times for healthcare services, solve resource allocation problems, and compare macro-scale disease control strategies that cannot be easily evaluated through randomized trials. Readings will complement the lectures and problem sets by offering critical perspectives from the public health history, sociology, and epidemiology. In-depth case studies from non-governmental organizations, departments of public health, and international agencies will drive the course. Open to upper-division undergraduate students.
Terms: Aut | Units: 4 | UG Reqs: WAY-AQR | Grading: Letter (ABCD/NP)
Instructors: Basu, S. (PI)

HUMBIO 154C: Cancer Epidemiology

Clinical epidemiological methods relevant to human research in cancer will be the focus. The concepts of risk; case control, cohort, and cross-sectional studies; clinical trials; bias; confounding; interaction; screening; and causal inference will be introduced and applied. Social, political, economic, and ethical controversies surrounding cancer screening, prevention, and research will be considered. Human Biology 154 courses can be taken separately or as a series
Terms: Win | Units: 4 | UG Reqs: WAY-AQR | Grading: Letter or Credit/No Credit

LAWGEN 116N: Guns, Drugs, Abortion, and Empirical Evaluation of Law and Policy

Guns, Drugs, Abortion, Capital Punishment, Policing and Prisons, and Other Uncontroversial Topics in the Empirical Evaluation of Law and Policy Do guns make us safer? Can mass shootings be stopped? What is the true cost of the war on drugs and is legalization the answer? Why does the US have the most prisoners in the world and what are the social ramifications? Did the legalization of abortion reduce crime in the 1990s? Did capital punishment? Is the criminal justice system racially biased? These are some of the questions we will address by reading major empirical studies evaluating the impact of law and policy in the arena of criminal justice. This course has been modified from my law school course so that it is accessible to those with little or no statistical or economic background but who are willing to grapple with the intuitions behind such studies, which will be a main focus of the course readings. The seminar should appeal to anyone interested in understanding core issues in criminal justice policy, the challenges in answering empirical questions with data, and the intuition behind the statistical techniques that define the credibility revolution in empirical evaluation. The goal is to help students be more aware that many beliefs and policy positions are based on factual premises for which the empirical support is weak or nonexistent, or even directly contradictory, and how better to empirically ascertain truths about the world and align them with our policy preferences. Successful completion of the course will enable students to more effectively understand and critically evaluate the strengths and weaknesses of the empirical studies that constantly appear in the media and policy discourse, to comprehend the challenges in establishing true causal relationships in the fields of law, policy, and medicine, and to better understand how ideologues and motivated researchers contribute to the vast array of conflicting studies in these domains.
Terms: Aut | Units: 3 | UG Reqs: WAY-AQR, WAY-SI | Grading: Letter or Credit/No Credit
Instructors: Donohue, J. (PI)

MATH 114: Introduction to Scientific Computing (CME 108)

Introduction to Scientific Computing Numerical computation for mathematical, computational, physical sciences and engineering: error analysis, floating-point arithmetic, nonlinear equations, numerical solution of systems of algebraic equations, banded matrices, least squares, unconstrained optimization, polynomial interpolation, numerical differentiation and integration, numerical solution of ordinary differential equations, truncation error, numerical stability for time dependent problems and stiffness. Implementation of numerical methods in MATLAB programming assignments. Prerequisites: MATH 51, 52, 53; prior programming experience (MATLAB or other language at level of CS 106A or higher).nGraduate students should take it for 3 units and undergraduate students should take it for 4 units.
Terms: Win, Sum | Units: 3 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR | Grading: Letter or Credit/No Credit

MATSCI 190: Organic and Biological Materials (MATSCI 210)

Unique physical and chemical properties of organic materials and their uses.The relationship between structure and physical properties, and techniques to determine chemical structure and molecular ordering. Examples include liquid crystals, dendrimers, carbon nanotubes, hydrogels, and biopolymers such as lipids, protein, and DNA. Prerequisite: Thermodynamics and ENGR 50 or equivalent. Undergraduates register for 190 for 4 units; graduates register for 210 for 3 units.
Terms: Spr | Units: 3-4 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-SMA | Grading: Letter or Credit/No Credit

MS&E 107: Interactive Management Science (MS&E 207)

Analytical techniques such as linear and integer programming, Monte Carlo simulation, forecasting, decision analysis, and Markov chains in the environment of the spreadsheet. Probability management. Materials include spreadsheet add-ins for implementing these and other techniques. Emphasis is on building intuition through interactive modeling, and extending the applicability of this type of analysis through integration with existing business data structures.
Terms: Aut | Units: 3 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR | Grading: Letter or Credit/No Credit
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