An MS Degree in Data Analytics and Quantitative Analysis from the Carnegie Mellon University has consistently made its place among the top global universities. Almost every field of inquiry must grapple with statistical problems, and the tools of statistical theory and data analysis you will develop in the Statistics minor (or Additional Major) will give you a critical edge. **Must take the Intermediate Data Analysis requirement prior to 36-401, if not, an additionalAdvanced Analysis and Methodology course is required. In addition, Statistics majors gain experience in applying statistical tools to real problems in other fields and learn the nuances of interdisciplinary collaboration. Average SAT: 1510 The average SAT score composite at Carnegie Mellon is a 1510 on the 1600 SAT scale. The Department of Statistics and Data Science offers advanced courses that focus on specific statistical applications or advanced statistical methods. CMU is a global leader in creating successful startup businesses. The most up-to-date information on CMU's COVID-19 mitigation requirements can be found here . Students in the Statistics and Machine Learning program develop and master a wide array of skills in computing, mathematics, statistical theory, and the interpretation and display of complex data. If a waiver or substitution is made in the home department, it is not automatically approved in the Department of Statistics and Data Science. The program is geared toward students interested in statistical computation, data science, and "big data" problems. 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. At Carnegie Mellon, the Chemical Engineering curricula brings together a deep understanding of molecular properties and process design to develop energy-efficient and sustainable manufacturing processes. 36-236 is the standard (and recommended) introduction to statistical inference. in Economics and Statistics are the following: Note: Passing the MSC 21-120 assessment test is an acceptable alternative to completing 21-120. These core courses involve extensive analysis of real data with emphasis on developing the oral and writing skills needed for communicating results. Students are advised to begin planning their curriculum (with appropriate advisors) as soon as possible. This flexible program helps you master both the theory and practice of statistics. The final authority in such decisions rests there. Students who elect Statistics (Mathematical Science Track) as an additional major must fulfill all Statistics(Mathematical Science Track) degree requirements. Designed for those with a strong interest in the empirical analysis of economic data, this program will give you a solid foundation in the theories and methods of both data science and economics. 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. These core courses involve extensive analysis of real data with emphasis on developing the oral and writing skills needed for communicating results. In many of these cases, the student will need to take additional courses to satisfy the Economics and Statistics major requirements. 36-200 draws examples from many fields and satisfy the Dietrich College Core Requirement in Statistical Reasoning. The requirements for the Major in Statistics are detailed below and are organized by categories #1-7. These situations may have additional application requirements. Advancing the state of knowledge across science, engineering, and policy related to particulate matter in the atmosphere and actively influencing related environmental policy. Toggle Department of Athletics and Physical Education, Toggle Reserve Officers' Training Corps (ROTC), Toggle Department of Biomedical Engineering, Toggle Department of Chemical Engineering, Toggle Department of Civil and Environmental Engineering, Toggle Department of Electrical and Computer Engineering, Toggle Department of Engineering and Public Policy, Toggle Department of Materials Science and Engineering, Toggle Department of Mechanical Engineering, Toggle Dietrich College of Humanities and Social Sciences, Toggle Institute for Politics and Strategy, Toggle Department of Social and Decision Sciences, Toggle Department of Statistics and Data Science, Toggle Department of Mathematical Sciences, Toggle Undergraduate Business Administration Program, Department of Statistics and Data Science, assessment test is an acceptable alternative to completing, *Or extra data analysis course in Statistics. in Economics and Statistics is jointly advised by the Department of Statistics and Data Science and the Undergraduate Economics Program. Other courses emphasize examples inengineering and architecture (36-220) and the laboratory sciences (36-247). 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. Students graduate in December. (Note: A score of 5 on the Advanced Placement (AP) Exam in Statistics may be used to waive this requirement). This is based on the school's average score. The linear algebra requirement is a prerequisite for the course 36-401 Students are advised to begin planning their curriculum (with appropriate advisors) as soon as possible. The course requirement is at least 4 courses and at least 14 credit hours. The Economics and Statistics major would then total 201-211 units. The Department augments all these strengths with a friendly, energetic working environment and exceptional computing resources. for 36-235 Students mostly do this through projects in specific courses, such as36-290,36-303, 36-490, 36-493,and/or36-497. To submit the application, you'll need to do the following: answer required questions within the online application form upload required essay and rsum register each recommender's name and email address enter test date and registration number for any required standardized test (s) Once the concentration area is approved, any changes made to the previously agreed upon coursework require re-approval by the Undergraduate Advisor. Keep in mind that the program is flexible and can support many other possible schedules. Students in the Bachelor of Science program develop and master a wide array of skills in computing, mathematics, statistical theory, and the interpretation and display of complex data. Or extra data analysis course in Statistics. By the end of the first semester, all students must select at least one area of concentration Systems, Analytics, or Human-Centered Data Science which governs thecourses taken after the first semester. 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. is the standard (and recommended) introduction to probability, 36-219 Statistics Majors and Minors seeking substitutions or waivers should speak to the Academic Advisor in Statistics. The curriculum provides both breadth and depth of training in computational biology, and is built on a solid foundation of biology, computer science, statistics and machine learning (data sciences). in Computer Science must take a minimum of 360 units in the following categories: Computer Science, Mathematics/Probability, Engineering and Natural Sciences, Humanities and Arts, Required Minor, Computing @ Carnegie Mellon and Free Electives. The theory of probability gives a mathematical description of the randomness inherent in our observations. Requirements The School of Computer Science requires the following for all applications: Talented graduate students join the department from around the world, and add a unique dimension to the department's intellectual life. Jointly administered by the Department of Statistics & Data Science and the Undergraduate Economics Program, the major's curriculum provides students with a solid foundation in the theories and methods of both fields. The Department of Statistics and Data Science does not provide approval or permission for substitution or waiver of another department's requirements. 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. Majors in many other programs would naturally complement a Statistics Major, including Tepper's undergraduate business program, Social and Decision Sciences, Policy and Management, and Psychology. The PDF will include all information unique to this page. A maker. Students interested in pursuing a PhD in Statistics or Machine Learning (or related programs) after completing their undergraduate degree are strongly recommended to take additional Mathematics courses. Samantha Nielsen, Associate Director of Academic Programs Although 21-240 Matrix Algebra with Applications is recommended for Statistics majors, students interested in PhD programs should consider taking 21-241 Matrices and Linear Transformations or 21-242 Matrix Theory instead. *In each semester, "-----" represents other courses (not related to the major) which are needed in order to complete the 360 units that the degree requires. Students should consider taking more than one course from the list of Machine Learning electives provided under the Computing section. Admissions Requirements Students are required to hold a four-year undergraduate degree or equivalent from an accredited institution. Students interested in pursuing a PhD in Statistics or Biostatistics (or related programs) after completing their undergraduate degree are strongly recommended to pursue the Mathematical Statistics Track. Consult the Schedule of Classes each semester for course offerings and for any necessary pre-requisites or co-requisites. A critical part of statistical practice is understanding the questions being asked so that appropriate methods of analysis can be used. Mar 25 - Apr 16 thump, whoosh, rumble: CMU MFA Exhibition. Research in the department spans the gamut from pure mathematics to the hottest frontiers of science. Both majors and non-majors are welcome. Data analysis is the art and science of extracting insight from data. Updated on Apr 10, 2023 Carnegie Mellon University is a private global research university located in Pittsburgh, USA. Students should carefully check the course descriptions to determine if additional prerequisites are necessary. 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. (or equivalent), and 36-401. 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