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341 - 350 of 381 results for: VPGE::*

SOMGEN 211: Preparation and Practice: Science Policy

Through tailored lecture, case study, and a practical final project, academic and professional leaders will help you gain insight into the science policy industry and the skills necessary to succeed within the various positions and levels available within it. This course aims to demystify the U.S. science policy process and teach both how policy affects scientific funding and administration, and how science is used to create and influence the creation of law and policy in the U.S. This course will be taught i two parts. The first part, to be completed prior to the first class outlines the basic structure of the US government, and fundamental issues in US political system, and refresh students who haven't encountered basic civics since high school, this introductory material will cover the structure of the US government, the governance of key agencies, broad concepts of federalism and shared federal and power, the political party system, and a brief and general modern history of the rol more »
Through tailored lecture, case study, and a practical final project, academic and professional leaders will help you gain insight into the science policy industry and the skills necessary to succeed within the various positions and levels available within it. This course aims to demystify the U.S. science policy process and teach both how policy affects scientific funding and administration, and how science is used to create and influence the creation of law and policy in the U.S. This course will be taught i two parts. The first part, to be completed prior to the first class outlines the basic structure of the US government, and fundamental issues in US political system, and refresh students who haven't encountered basic civics since high school, this introductory material will cover the structure of the US government, the governance of key agencies, broad concepts of federalism and shared federal and power, the political party system, and a brief and general modern history of the role of science in policy making. The short class online class will acquaint students with the structure of law, regulations and other appropriate policy documents. This online class will be available asynchronously two weeks prior to the live course. A faculty member will moderate this course and give feedback to students on short assignments designed to ensure they understand basic concepts and are prepared for the live class. nThe second part, taught over five days in 3-hour in-class sessions, will review four key concepts: 1) who's who and how they work. The structure and function of the executive branch and its control over science-based agencies, and the legislative oversight and budgeting of these agencies. 2) The policy making process. The policy making process, and the role of science in creating policy. This section will include broad overviews of the legislative process, competing political theory, and risk/assessment/risk management models, as well as discussion of the role of scientists as agency employees and officials, and scientists as experts, interested parties and reviewers. 3) Government funding science. the funding of science by government, including the mechanisms, processes and dominant theories of science funding, as well as the practical and political tensions around science funding, and the reporting and accountability standards to which recipients are subject. 4) Issues, theories and trends in science and policy. The ecology of innovation and policy in the US. Sometimes referred to as the emerging "science of science policy". This final section will review a variety of cross-cutting issues in science policy development, including innovation theory, the role of uncertainty, and a discussion of the government's role as a developer and repository of science data, and other current topics in the relationship between science and government.
Last offered: Spring 2019 | Repeatable for credit

SOMGEN 223: Introduction to R for data analysis

Introduction to R, an open-source programming language for statistical computing and graphics. Topics include: the basics of the R language and RStudio environment, data inspection and manipulation, graphics for data visualization, and tools for reproducible research. Interactive format combining lecture and hands-on computer lab, with time to work on your own data. Numerous in-class and homework exercises to build effective skills. Examples will be drawn from different areas of biology and medicine.
Terms: Aut, Win, Spr | Units: 3

SOMGEN 275: Leading Value Improvement in Health Care Delivery

Successful leaders on the journey to better care delivery methods with lower total spending inevitably face challenges. What confluence of attitudes, values, strategy, and events allows them to prevail? Contexts will include public policy, entrepreneurship and early stage investing, care delivery innovations, and health care system management to improve the value of care. Course faculty and guests will consist of nationally recognized leaders, innovators, and change agents. The course is open to any member of the Stanford community aspiring to lead value improvement in health care delivery including medical, MBA, law, and graduate students, as well as undergraduates, postdoctoral candidates, and medical center trainees. May be repeated for credit.
Terms: Aut | Units: 1 | Repeatable for credit

SOMGEN 282: The Startup Garage: Design (CHEMENG 482)

(Same as STRAMGT 356) The Startup Garage is an experiential lab course that focuses on the design, testing and launch of a new venture. Multidisciplinary student teams work through an iterative process of understanding user needs, creating a point of view statement, ideating and prototyping new product and services and their business models, and communicating the user need, product, service and business models to end-users, partners, and investors. In the autumn quarter, teams will: identify and validate a compelling user need and develop very preliminary prototypes for a new product or service and business models. Students form teams, conduct field work and iterate on the combination of business model -- product -- market. Teams will present their first prototypes (business model - product - market) at the end of the quarter to a panel of entrepreneurs, venture capitalists, angel investors and faculty.
Terms: Aut | Units: 4

SOMGEN 284: The Startup Garage: Testing and Launch (CHEMENG 484)

This is the second quarter of the two-quarter series. In this quarter, student teams expand the field work they started in the fall quarter. They get out of the building to talk to potential customers, partners, distributors, and investors to test and refine their business model, product/service and market. This quarter the teams will be expected to develop and test a minimally viable product, iterate, and focus on validated lessons on: the market opportunity, user need and behavior, user interactions with the product or service, business unit economics, sale and distribution models, partnerships, value proposition, and funding strategies. Teams will interact with customers, partners, distributors, investors and mentors with the end goal of developing and delivering a funding pitch to a panel of entrepreneurs, venture capitalists, angel investors and faculty.
Terms: Win | Units: 4

STATS 200: Introduction to Statistical Inference

Terms: Aut, Win | Units: 3

STATS 202: Data Mining and Analysis

Data mining is used to discover patterns and relationships in data. Emphasis is on large complex data sets such as those in very large databases or through web mining. Topics: decision trees, association rules, clustering, case based methods, and data visualization. Prereqs: Introductory courses in statistics or probability (e.g., Stats 60), linear algebra (e.g., Math 51), and computer programming (e.g., CS 105).
Terms: Aut, Sum | Units: 3

STATS 203: Introduction to Regression Models and Analysis of Variance

Modeling and interpretation of observational and experimental data using linear and nonlinear regression methods. Model building and selection methods. Multivariable analysis. Fixed and random effects models. Experimental design. Prerequisites: a post-calculus introductory probability course, e.g. STATS 116. In addition, a co-requisite post-calculus mathematical statistics course, e.g. STATS 200, basic computer programming knowledge, and some familiarity with matrix algebra.
Terms: Win | Units: 3

STATS 203V: Introduction to Regression Models and Analysis of Variance

Modeling and interpretation of observational and experimental data using linear and nonlinear regression methods. Model building and selection methods. Multivariable analysis. Fixed and random effects models. Experimental design. This course is offered remotely only via video segments (MOOC style). TAs will host remote weekly office hours using an online platform such as Zoom. Prerequisites: a post-calculus introductory probability course, e.g. STATS 116. In addition, a co-requisite post-calculus mathematical statistics course, e.g. STATS 200, basic computer programming knowledge, and some familiarity with matrix algebra.
Terms: Sum | Units: 3

STATS 204: Sampling

How best to take data and where to sample it. Examples include surveys and sampling from data warehouses. Emphasis is on methods for finite populations. Topics: simple random sampling, stratified sampling, cluster sampling, ratio and regression estimators, two stage sampling.
Terms: Spr | Units: 3
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