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51 - 60 of 151 results for: all courses

EARTHSYS 110: Introduction to the Foundations of Contemporary Geophysics (GEOPHYS 110)

Introduction to the foundations of contemporary geophysics. Topics drawn from broad themes in: whole Earth geodynamics, geohazards, natural resources, and environment. In each case the focus is on how the interpretation of a variety of geophysical measurements (e.g., gravity, seismology, heat flow, electromagnetics, and remote sensing) can be used to provide fundamental insight into the behavior of the Earth. The course will include a weekend field trip. Prerequisite: CME 100 or MATH 51, or co-registration in either.
Terms: Spr | Units: 3 | UG Reqs: GER: DB-NatSci, WAY-AQR, WAY-SMA | Grading: Letter or Credit/No Credit

EARTHSYS 113: Earthquakes and Volcanoes (GEOPHYS 90)

Is the "Big One" overdue in California? What kind of damage would that cause? What can we do to reduce the impact of such hazards in urban environments? Does "fracking" cause earthquakes and are we at risk? Is the United States vulnerable to a giant tsunami? The geologic record contains evidence of volcanic super eruptions throughout Earth's history. What causes these gigantic explosive eruptions, and can they be predicted in the future? This course will address these and related issues. For non-majors and potential Earth scientists. No prerequisites. More information at: https://stanford.box.com/s/zr8ar28efmuo5wtlj6gj2jbxle76r4lu
Terms: Spr | Units: 3 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-SMA | Grading: Letter or Credit/No Credit

EARTHSYS 141: Remote Sensing of the Oceans (EARTHSYS 241, ESS 141, ESS 241, GEOPHYS 141)

How to observe and interpret physical and biological changes in the oceans using satellite technologies. Topics: principles of satellite remote sensing, classes of satellite remote sensors, converting radiometric data into biological and physical quantities, sensor calibration and validation, interpreting large-scale oceanographic features.
Terms: Win | Units: 3-4 | UG Reqs: GER: DB-NatSci, WAY-AQR | Grading: Letter or Credit/No Credit
Instructors: Arrigo, K. (PI)

EARTHSYS 142: Remote Sensing of Land (EARTHSYS 242, ESS 162, ESS 262)

The use of satellite remote sensing to monitor land use and land cover, with emphasis on terrestrial changes. Topics include pre-processing data, biophysical properties of vegetation observable by satellite, accuracy assessment of maps derived from remote sensing, and methodologies to detect changes such as urbanization, deforestation, vegetation health, and wildfires.
Terms: Win | Units: 4 | UG Reqs: WAY-AQR | Grading: Letter or Credit/No Credit
Instructors: Lyons, E. (PI)

EARTHSYS 144: Fundamentals of Geographic Information Science (GIS) (ESS 164)

Survey of geographic information including maps, satellite imagery, and census data, approaches to spatial data, and tools for integrating and examining spatially-explicit data. Emphasis is on fundamental concepts of geographic information science and associated technologies. Topics include geographic data structure, cartography, remotely sensed data, statistical analysis of geographic data, spatial analysis, map design, and geographic information system software. Computer lab assignments. All students are required to attend a weekly lab session.
Terms: Aut | Units: 3-4 | UG Reqs: GER: DB-NatSci, WAY-AQR | Grading: Letter or Credit/No Credit
Instructors: Lyons, E. (PI)

EARTHSYS 152: Marine Chemistry (EARTHSYS 252, ESS 152, ESS 252)

Introduction to the interdisciplinary knowledge and skills required to critically evaluate problems in marine chemistry and related disciplines. Physical, chemical, and biological processes that determine the chemical composition of seawater. Air-sea gas exchange, carbonate chemistry, and chemical equilibria, nutrient and trace element cycling, particle reactivity, sediment chemistry, and diagenesis. Examination of chemical tracers of mixing and circulation and feedbacks of ocean processes on atmospheric chemistry and climate. Designed to be taken concurrently with Biological Oceanography (ESS/ EARTHSYS 151/251)
Terms: Spr | Units: 3-4 | UG Reqs: WAY-AQR, WAY-SMA | Grading: Letter or Credit/No Credit

EARTHSYS 185: Feeding Nine Billion

Feeding a growing and wealthier population is a huge task, and one with implications for many aspects of society and the environment. There are many tough choices to be made- on fertilizers, groundwater pumping, pesticide use, organics, genetic modification, etc. Unfortunately, many people form strong opinions about these issues before understanding some of the basics of how food is grown, such as how most farmers currently manage their fields, and their reasons for doing so. The goal of this class is to present an overview of global agriculture, and the tradeoffs involved with different practices. Students will develop two key knowledge bases: basic principles of crop ecology and agronomy, and familiarity with the scale of the global food system. The last few weeks of the course will be devoted to building on this knowledge base to evaluate different future directions for agriculture.
Terms: Win | Units: 4-5 | UG Reqs: WAY-AQR | Grading: Letter or Credit/No Credit
Instructors: Lobell, D. (PI)

ECON 47: Media Markets and Social Good

This class will apply tools from economics and related social sciences to study the functioning of media markets and their impact on society. The guiding question will be: when and how do media best serve the social good? Topics will include the economics of two-sided markets, media bias, polarization, social media, fake news, advertising, propaganda, effects of media on children, media and crime, and the role of media in corruption, protests and censorship. The course will give students a non-technical introduction to social science empirical methods, including regression analysis, causal inference, experimental and quasi-experimental methods, and machine learning.
Terms: Spr | Units: 5 | UG Reqs: WAY-AQR, WAY-SI | Grading: Letter or Credit/No Credit
Instructors: Gentzkow, M. (PI)

ECON 102A: Introduction to Statistical Methods (Postcalculus) for Social Scientists

Probabilistic modeling and statistical techniques relevant for economics. Concepts include: probability trees, conditional probability, random variables, discrete and continuous distributions, correlation, central limit theorems, point estimation, hypothesis testing and confidence intervals for both one and two populations. Prerequisite: MATH 20 or equivalent.
Terms: Aut, Win | Units: 5 | UG Reqs: GER:DB-Math, WAY-AQR, WAY-SI | Grading: Letter or Credit/No Credit
Instructors: McKeon, S. (PI)

ECON 102B: Applied Econometrics

Hypothesis tests and confidence intervals for population variances, chi-squared goodness-of-fit tests, hypothesis tests for independence, simple linear regression model, testing regression parameters, prediction, multiple regression, omitted variable bias, multicollinearity, F-tests, regression with indicator random variables, simultaneous equation models and instrumental variables. Topics vary slightly depending on the quarter. Prerequisites: Econ 102A or equivalent. Recommended: computer experience (course often uses STATA software to run regressions).
Terms: Win, Spr | Units: 5 | UG Reqs: WAY-AQR, WAY-SI | Grading: Letter or Credit/No Credit
Instructors: McKeon, S. (PI)
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