Carnegie Mellon's Department of Electrical and Computer Engineering is widely recognized as one of the best programs in the world. The former uses probability theory to build and analyze mathematical models of data in order to devise methods for making effective predictions and decisions in the face of uncertainty. The second schedule is an example of the case when a student enters the Minor through 36-235 and 36-236 (and therefore skips the beginning data analysis course). Are you ready for Carnegie Mellon? The PDF will include all information unique to this page. Were ready for you, too. The courses cover similar topics but differ slightly in the examples they emphasize. At the same time, the faculty is firmly dedicated to undergraduate education. This program is geared towards students interested in statistical computation, data science, or Big Data problems. Rebecca Nugent, Department Head Students come to Carnegie Mellon to learn, create and innovate with the very best. Students seeking transfer credit for those requirements from substitute courses (at Carnegie Mellon or elsewhere) should seek permission from their advisor in the department setting the requirement. (i) In order to meet the prerequisite requirements, a grade of at least a C is required in36-235 Decide which plan is best for you Additional Application Information These situations may have additional application requirements. The Beginning Data Analysis courses give a hands-on introduction to the art and science of data analysis. All MCDS students must complete 144 units of graduate study which satisfy the following curriculum: Professional Preparation a 16-month degree consisting of study for fall and spring semesters, a summer internship, and fall semester of study. ), and the laboratory sciences (36-247 The Department augments all these strengths with a friendly, energetic working environment and exceptional computing resources. Complete one of the following sequences of mathematics courses at Carnegie Mellon, each of which provides sufficient preparation in calculus: 21-241 There is a variety of research projects in the department as well, and students who would like to pursue working on a project with faculty will need to contact that faculty directly to discuss that possibility. Carnegie Mellon University and ETH Zurich are two of the world's top universities for computer science, ranked 9th and 52nd in the QS World University Rankings 2023, respectively. During the first two semesters in the program, all students take a set of five (5) required core courses: 11-637 Fundamentals of Computational Data Science, 15-619 Cloud Computing, 10-601 Machine Learning, 05-839 Interactive Data Science, and 11-631 Data Science Seminar. Non-majors are eligible to take most of our courses, and indeed, they are required to do so by many programs on campus. **The linear algebra requirement needs to be completed before taking 36-401 Modern Regression. One goal of the Statistics program is to give students experience with statistical research. Indeed, the tools of Statistics apply to problems in almost every area of human activity where data are collected. Courses within Statistics can be any 300 or 400 level course (that is not used to satisfy any other requirement for the statistics major). Each semester comprises a minimum of 48 units. (or equivalent), 36-236 With respect to double-counting courses, it is departmental policy that students must have at least six courses [three Economics (73-xxx) and three Statistics (36-xxx)] that do not count for their primary major. ). If students do not have at least five, they will need to take additional advanced data analysis electives. The following sample programs illustrate three (of many) ways to satisfy the requirements of the Statistics Major. They leave with the passion, connections, credentials and lifelong friends who will help them change the world. My unwavering . Students are advised to begin planning their curriculum (with appropriate advisors) as soon as possible. Youre a scientist. (or equivalent) and 36-401. **It is possible to substitute36-226or36-326(honors course) for36-236. A technologist. The Advanced Data Analysis courses draw on students' previous experience with data analysis and understanding of statistical theory to develop advanced, more sophisticated methods. Mathematics is the language in which statistical models are described and analyzed, so some experience with basic calculus and linear algebra is an important component for anyone pursuing a program of study in Statistics. Complete one of the following three sequences of mathematics courses at Carnegie Mellon, each of which provides sufficient preparation in calculus: Complete oneof the following three courses: * It is recommended that students complete the calculus requirement during their freshman year. Advanced mathematics courses are encouraged. Ask FRIDA to paint a picture, and it gets to work putting brush to canvas. There are many ways to get involved in Statistics at Carnegie Mellon: Statistics consists of two intertwined threads of inquiry: Statistical Theory and Data Analysis. The Department of Statistics and Data Science offers advanced courses that focus on specific statistical applications or advanced statistical methods. If you're closer to the 1380, you're likely going to have a tougher time getting accepted. The first schedule uses calculus sequence 1. **It is possible to substitute36-226or36-326(honors course) for36-236. But this attitude is becoming less and less prevalent, and today there is much to be gained from a strong working knowledge of computational tools. RON YURKO, Assistant Teaching Professor Ph.D., GEORGE T. DUNCAN, Professor of Statistics and Public Policy Ph.D., University of Minnesota; Carnegie Mellon, 1974, WILLIAM F. EDDY, John C. Warner Professor of Statistics Ph.D, Yale University; Carnegie Mellon, 1976, JOSEPH B. KADANE, Leonard J. 36-200 draws examples from many fields and satisfy the Dietrich College Core Requirement in Statistical Reasoning. Other courses emphasize examples inengineering and architecture (36-220 . An MS Degree in Data Analytics and Quantitative Analysis from the Carnegie Mellon University has consistently made its place among the top global universities. However, the Statistics Director of Undergraduate Studies will provide advice and information to the student's advisor about the viability of a proposed substitution. The Intermediate Data Analysis courses build on the principles and methods covered in the introductory course, and more fully explore specific types of data analysis methods in more depth. (36-235 (opens in new window). In addition, Statistics majors gain experience in applying statistical tools to real problems in other fields and learn the nuances of interdisciplinary collaboration. Must take prior to 36-401 Modern Regression, if not, an additional Advanced Statistics Elective is required. in Statistics (Statistics and Neuroscience Track), Additional Major in Statistics (Neuroscience Track), Additional Major in Statistics and Machine Learning, DietrichCollegeofHumanitiesandSocialSciences, http://www.stat.cmu.edu/academics/courselist, http://coursecatalog.web.cmu.edu/schools-colleges/dietrichcollegeofhumanitiesandsocialsciences/depar, http://www.stat.cmu.edu/~ryantibs/convexopt/, http://www.stat.cmu.edu/~aramdas/reproducibility19/, CMU Students are advised to begin planning their curriculum (with appropriate advisors) as soon as possible. Computational algorithms are sometimes treated as black-boxes, whose innards the statistician need not pay attention to. The degree can also be earned two different ways, depending on the length of time you spend working on it. Students seeking waivers may be asked to demonstrate mastery of the material. Students who maintain a quality point average of 3.25 overall may also apply to participate in the Dietrich College Senior Honors Program, for additional research experience. Please note that students who complete36-235are expected to take36-236to complete their theory requirements. The Department and Faculty The Department of Statistics & Data Science at Carnegie Mellon University is world-renowned for its contributions to statistical theory and practice. Note that these courses require an application. If a waiver or substitution is made in the home department, it is not automatically approved in the Department of Statistics and Data Science. in Statistics (Mathematical Sciences Track), Recommendations for Prospective PhD Students, Additional Major in Statistics (Mathematical Science Track), B.S. Other courses emphasize examples inengineering and architecture (36-220) and the laboratory sciences (36-247). With respect to double-counting courses, it is departmental policy that students must have at least five statistics courses that do not count for their primary major. Additional experience in programming and computational modeling is also recommended. We've got the resources to support you. Any 36-300 or 36-400 level course in Data Analysis that does not satisfy any other requirement for the Economics and Statistics Major may be counted as a Statistical Elective. This is particularly true if the other major has a complex set of requirements and prerequisites or when many of the other major's requirements overlap with the requirements for a Major in Statistics and Machine Learning. (For example, three members of the faculty have been awarded the COPSS medal, the highest honor given by professional statistical societies.) **It is possible to substitute36-226or36-326(honors course) for36-236. There is a variety of research projects in the department as well, and students who would like to pursue working on a project with faculty will need to contact that faculty directly to discuss that possibility. All three require the same total number of course credits split among required core courses, electives, data science seminar and capstone courses. However, keep in mind that the program is flexible enough to support many other possible schedules and to emphasize a wide variety of interests. Faculty, graduate students, and undergraduates interact regularly. The objective of the course is to expose students to important topics in statistics and/or interesting applications which are not part of the standard undergraduate curriculum. Before graduation, students are encouraged to participate in a research project under faculty supervision. should discuss options with an advisor. Special Topics rotate and new ones are regularly added. Many departments require Statistics courses as part of their Major or Minor programs. Students must take two advanced Economics elective courses (numbered 73-300 through 73-495, excluding 73-374 ) and two (or three - depending on previous coursework, see Section 3) advanced Statistics elective courses (numbered 36-303, 36-311, 36-313,36-315, 36-318, 36-46x, 36-490, 36-493or 36-497). Carnegie Mellon University attracts a certain type of student: motivated, inventive and driven to make a difference. Three courses (3) from one area of concentration curriculum (36 units), Three (3) MCDS Capstone courses (11-635, 11-634 and 11-632) (36 units), Two (2) Electives: any graduate level course 600 and above in the School of Computer Science (24 units). (i) In order to meet the prerequisite requirements, a grade of at least a C is required in 36-235 36-236is the standard (and recommended) introduction to statistical inference. This is based on the school's average score. Mar 6 - Dec 1 Inventing Shakespeare: Text, Technology, and the Four Folios Exhibit. Students who choose to take36-225instead will be required to take36-226afterward, they will not be eligible to take36-236. is tailored for engineers and computer scientists, 36-218is a more mathematically rigorous class for Computer Science students and more mathematically advanced (students need advisor approval to enroll),and 21-325 While not required, students are strongly encouraged to take advantage of professional development opportunities and/or coursework. Students pursuing an additional major in Science, Technology and Public Policy (STPP) must complete three sets of requirements: courses for the STPP additional major, courses for their traditional disciplinary major . The Department Statistics does not provide approval or permission for substitution or waiver of another department's requirements. You arestrongly encouraged to review the detailed curriculum requirements foreach concentration area, in order to determine the best fit given your preparationand background. This is a good choice for deepening understanding of statistical ideas and for strengthening research skills. 36-235 The department gives students research experience through various courses focused on real-world experiences and application. The latter involves techniques for extracting insights from complicated data, designs for accurate measurement and comparison, and methods for checking the validity of theoretical assumptions. Mar 30 Dickson Prize in Science Ceremony and Lecture: Richard Aslin. Make sure to consult your Statistics Minor advisor regarding double counting. The Minor (or Additional Major) in Statistics is a useful complement to a (primary) major in another Department or College. Statistics Majors and Minors seeking substitutions or waivers should speak to the Academic Advisor in Statistics. Students are rigorously trained in fundamentals of engineering, with a strong bent towards the maker culture of learning and doing. It is therefore essential to complete this requirement during your junior year at the latest. If students do not have at least three ECON and three STA classes, they will need to take additional advanced data analysis or economics electives, depending on where the double-counting issue is. In many of these cases, the student will need to take additional courses to satisfy the Statistics major requirements. . These courses are usually drawn from a single discipline of interest to the student and must be approved by the Statistics Undergraduate Advisor. The schedule uses calculus sequence 2, andan advanced data analysis elective (to replace the beginning data analysis course). Also recommended graduation, students are rigorously trained in fundamentals of engineering, with a strong bent towards maker! 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