Before registering, the student must submit an outline of the proposed work for approval by the supervisor and the chair of the Department. Advanced study in a specialized field under the supervision of a member of the department staff. May be repeated for credit.
Prerequisites: the instructors permission. Individual research and tutorial in archaeology for advanced graduate students.
Prerequisites: the instructors permission. Individual research and tutorial in physical anthropology for advanced graduate students.
Guided reading and research on a topic or in a field chosen by the student in consultation with a member of the faculty.
The biostatistical field is changing with new directions emerging constantly. Doing research in these new directions, which often involve large data and complex designs, requires advanced probability and statistics tools. The purpose of this new course is to collect these important probability methods and present them in a way that is friendly to a biostatistics audience. This course is designed for PhD students in Biostatistics. Its primary objective is to help the students achieve a solid understanding of these probability methods and develop strong analytical skills that are necessary for conducting methodological research in modern biostatistics. At the completion of this course, the students will a) have a working knowledge in Law of Large Numbers, Central Limit Theorems, martingale theory, Brownian motions, weak convergence, empirical process, and Markov chain theory; b) be able to understand the biostatistical literature that involves such methods; c) be able to do proofs that call for such knowledge.
Prerequisites: the instructors permission. Individual research in all divisions of anthropology and in allied fields for advanced graduate students
Prerequisites: the instructors permission. Individual research in all divisions of anthropology and in allied fields for advanced graduate students
Prerequisites: the instructors permission. Individual research in all divisions of anthropology and in allied fields for advanced graduate students
Prerequisite: Statistics G6105 (real analysis and probability theory), or the equivalent. A general introduction to mathematical statistics and statistical decision theory. Elementary decision theory, Bayes inference, Neyman-Pearson theory, hypothesis testing, uniformity, most powerful unbiased tests, confidence sets. Estimation: methods, theory, and asymptotic properties. Likelihood ratio tests, multivariate distribution. Elements of general linear hypothesis, invariance, nonparametric methods, sequential analysis.
An internship arranged through the Museum Anthropology program of 10 hrs/week (for 3 credits) or 20 hrs/week (for 6). Involves meaningful work, requires keeping a journal and writing a paper at the completion of the semester. Not to be taken without permission of the program directors, usually after completing the Museum Anthropology core courses.
What is realism and how does it relate to objectivity? In this course, we will consider a range of answers, with special attention to problems of value. We will begin by clarifying the nature of realism about a subject matter and arguments that might support it. We will then look at limitations of realism per se, and the need to supplement it with a distinct notion of objectivity. Next, we will consider arguments that “realist objectivism”, while attractive, is an untenable package. This will lead us to discuss anti-objectivist forms of realism and their deflationary methodological ramifications. Finally, we will look at the prospects for objectivity without realism, particularly in the evaluative case. We will conclude by sketching a neo-pragmatist metaphilosophical outlook.
An internship arranged through the Museum Anthropology program of 10 hrs/week (for 3 credits) or 20 hrs/week (for 6). Involves meaningful work, requires keeping a journal and writing a paper at the completion of the semester. Not to be taken without permission of the program directors, usually after completing the Museum Anthropology core courses.
Prerequisites: the instructors permission. Individual research and tutorial in archaeological method and theory for advanced graduate students.
Prerequisites: the instructors permission. Individual research and tutorial in archaeological method and theory for advanced graduate students.
Prerequisites: the instructors permission. Individual research and tutorial in archaeological method and theory for advanced graduate students.
The course is designed for entering doctoral students and provides a rigorous introduction to the fundamental theory of optimization. It examines optimization theory in continuous, deterministic settings, including optimization in Euclidean as well as in more general, infinite-dimensional vector spaces. The course emphasizes unifying themes (such as optimality conditions, Lagrange multipliers, convexity, duality) that are common to all of these areas of mathematical optimization. Applications across a range of problem areas serve to illustrate and motivate the theory that is developed. Additionally, review sessions explaining how to solve complex optimization problems using CVX and Python are offered.
FILM AF 9120 TV Revision
The goal of TV Revision is to bring in a completed pilot and then completely revise it in one semester. Students will initially present their full scripts for feedback in class discussion, then map a plan for rewriting with their instructor. Deadlines throughout the semester will focus on delivery of revised pages.
The work can range from an intensive page 1 rewrite to focus on selected areas in a script. Reading of all scripts in the workshop and participation in class discussion is required. There is an application process to select students for the class.
This is an advanced course for first-year Ph.D. students in Biostatistics. The aim is to provide a solid foundation of the theory behind linear models and generalized linear models. More emphasis will be placed on concepts and theory with mathematical rigor. Topics covered including linear regression models, logistic regression models, generalized linear regression models and methods for the analysis contingency tables.
This course is designed to increase student knowledge of Psychiatric Nurse Practitioner Case Narrative writing, and DNP competencies. Students will use case narratives as a framework to synthesize knowledge, assessment, and clinical thinking skills. Students will explore Social Justice competency, Competency D3C3 in depth. Students will develop a treatment intervention that identify and challenge biases that contribute to health disparities.
May be repeated for credit. Selected topics in applied physics. Topics and instructors change from year to year.
This fourteen-week elective, open to Research Arts Screen & TV Writing students, will provide vital directing advisement to Portfolio films. It covers pre-production and director’s prep.
Students get together to discuss the paper which will be presented at the IEOR-DRO seminar. One group of students (~2 students) presents. A faculty member is present to guide and facilitate the discussion. Students are evaluated on their effort in leading one of the discussions and participating in the other discussions
Continuation of N9150.
This is a Law School course. For more detailed course information, please go to the Law School Curriculum Guide at: http://www.law.columbia.edu/courses/search
In this course, students will apply the concepts and methods introduced in Statistical Practices and Research for Interdisciplinary Science (SPRIS) I to a real research setting. Each student will be paired with a Biostatistics faculty member. The student will participate in one of the mentor’s collaborative projects to learn how to be an effective member of an interdisciplinary team. The relationship will mimic that between a medical resident and an attending physician. The SPRIS II experience will vary depending on the assigned faculty member, but all students will gain exposure to preparing collaborative grant applications, designing research studies, analyzing real data, interpreting and presenting results, and writing manuscripts. Mentors will help to develop the student’s data intuition skills, ability to ask good research questions, and leadership qualities. Where necessary, students may replicate projects already completed by the faculty mentor to gain experience.
For appropriately qualified students wishing to enrich their programs by undertaking literature reviews, special studies, or small group instruction in topics not covered in formal courses.
This course is restricted to PhD in Sustainable Development
Departmental colloquium in statistics.