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81 - 90 of 134 results for: all courses

GEOPHYS 110: Introduction to the foundations of contemporary geophysics (EARTHSYS 110)

Introduction to the foundations of contemporary geophysics. Topics drawn from broad themes in: whole Earth geodynamics, geohazards, natural resources, and enviroment. 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. Prerequisite: CME 100 or MA TH 51, or co-registration in either.
Terms: Aut | Units: 3 | UG Reqs: GER: DB-NatSci, WAY-AQR, WAY-SMA | Grading: Letter or Credit/No Credit

GEOPHYS 130: Introductory Seismology

Introduction to seismology including: elasticity and the wave equation, P, S, and surface waves, dispersion, ray theory, reflection and transmission of seismic waves, seismic imaging, large-scale Earth structure, earthquake location, earthquake statistics and forecasting, magnitude scales, seismic source theory.
Terms: not given this year | Units: 3 | UG Reqs: GER: DB-NatSci, WAY-AQR, WAY-SMA | Grading: Letter or Credit/No Credit

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

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)

GEOPHYS 160: D^3: Disasters, Decisions, Development

This class connects the science behind natural disasters with the real-world constraints of disaster management and development. In each iteration of this class we will focus on a specific, disaster-prone location as case study. By collaborating with local stakeholders we will explore how science and engineering can make a make a difference in reducing disaster risk in the future. Offered every other year.
Terms: not given this year | Units: 3-5 | UG Reqs: WAY-AQR, WAY-SMA | Grading: Letter (ABCD/NP)

GS 1: Introduction to Geology (EARTHSYS 11)

Why are earthquakes, volcanoes, and natural resources located at specific spots on the Earth surface? Why are there rolling hills to the west behind Stanford, and soaring granite walls to the east in Yosemite? What was the Earth like in the past, and what will it be like in the future? Lectures, hands-on laboratories, in-class activities, and one field trip will help you see the Earth through the eyes of a geologist. Topics include plate tectonics, the cycling and formation of different types of rocks, and how geologists use rocks to understand Earth's history.
Terms: Win | Units: 5 | UG Reqs: GER: DB-NatSci, WAY-AQR, WAY-SMA | Grading: Letter or Credit/No Credit
Instructors: Sperling, E. (PI)

GS 42: Landscapes and Tectonics of the San Francisco Bay Area (EARTH 42)

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 51: Big Data for Biologists - Decoding Genomic Function

Biology and medicine are becoming increasingly data-intensive fields. This course is designed to introduce students interested in human biology and related fields to methods for working with large biological datasets. There will be in-class activities analyzing real data that have revealed insights about the role of the genome and epigenome in health and disease. For example, we will explore data from large-scale gene expression and chromatin state studies. The course will provide an introduction to the relevant topics in biology and to fundamental computational skills such as editing text files, formatting and storing data, visualizing data and writing data analysis scripts. Students will become familiar with both UNIX and Python. This course is designed at the introductory level. Previous university-level courses in biology and programming experience are not required.
Terms: Aut | Units: 3 | UG Reqs: WAY-AQR | Grading: Letter or Credit/No Credit

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: not given this year | 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)
Instructors: Kurina, L. (PI)

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. Cardinal Course certified by the Haas Center
Terms: Aut, Win | Units: 3 | UG Reqs: GER:DB-Math, WAY-AQR | Grading: Letter or Credit/No Credit
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