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. . **It is possible to substitute36-226or36-326(honors course) in place of36-236. The Bachelor of Science in Statistics in the Dietrich College of Humanities and Social Sciences (DC) is a broad-based, flexible program that helps you master both the theory and practice of Statistics. This course is therefore recommended for students in the College. Were ready for you, too. **It is possible to substitute36-226 or36-326 for36-236. Students graduate in May. The first schedule uses calculus sequence 1, and 36-202to satisfy the intermediate data analysis requirement. 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) CMU Energy Week 2023: March 21-24. All three require the same total number of course credits split among required core courses, electives, data science seminar and capstone courses. While these courses are not in Statistics, the concentration area must complement the overall Statistics degree. The requirements for the B.S. Carnegie Mellon University (CMU) is a private research university in Pittsburgh, Pennsylvania.The institution was originally established in 1900 by Andrew Carnegie as the Carnegie Technical Schools.In 1912, it became the Carnegie Institute of Technology and began granting four-year degrees. Current Computer Science Undergraduate Curriculum 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. Statistical modeling in practice nearly always requires computation in one way or another. (or equivalent), 36-236 Browse all current Department of Statistics & Data Sciencecurriculums and courses. Students should also take advantage of the Career and Professional Development Center. Complete one of the following sequences of mathematics courses at Carnegie Mellon, each of which provides sufficient preparation in calculus: 21-241 is the standard (and recommended) introduction to probability, 36-219 Submit your application for the Dietrich College of Humanities and Social Sciences. Doctoral Programs In the School of Computer Science, we believe that Ph.D. students thrive in a flexible environment that considers their background and experience, separates funding from advising, and encourages interdisciplinary exploration. is tailored for engineers and computer scientists, isa more mathematically rigorous class for Computer Science students and more mathematically advanced (students need advisor approval to enroll), and. In many of these cases, the student will need to take additional courses to satisfy the Statistics major requirements. Carnegie Mellon University 300 S. Craig Street, Suite 209 Pittsburgh, PA 15213 nicolewi@cs.cmu.edu Phone: 412-268-7971 Fax: 412-268-9433 Footer Home About Academics Careers Giving News & Events People Research Follow Us Facebook Instagram LinkedIn Twitter YouTube Calendar Human-Computer Interaction Institute Many departments require Statistics courses as part of their Major or Minor programs. Application Status, Dietrich College of Humanities & Social Sciences, Academic Requirements & College-Level Work, Resources for College Counseling Partners. More events. statadvising@andrew.cmu.edu. The entire faculty, junior and senior, teach courses at all levels. The Minor (or Additional Major) in Statistics is a useful complement to a (primary) major in another Department or College. * Note: The concentration/track requirement is only for students whose primary major is statistics and has no other additional major or minor. In addition, you will need to submit standardized test scores. The Advanced Data Analysis and Methodology courses draw on students' previous experience with data analysis and understanding of statistical theory to develop advanced, more sophisticated methods. Keep in mind that the program is flexible and can support other possible schedules (see footnotes below the schedule). This schedule has more emphasis on statistical theory and probability. Bachelor of Science (Jointly offered by the Undergraduate Economics Program). ***This is not an exhaustive list. The program can be tailored to prepare you for later graduate study in statistics, or to complement your interests in almost any field, including psychology, physics, biology, history, business, information systems and computer science. Students should consider 36-326 Mathematical Statistics (Honors) as an alternative to 36-236 With respect to double-counting courses, it is departmental policy that students must have at least three statistics courses (36-xxx) that do not count for their primary major. 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. Pittsburgh, PA 15213 Students who maintain a quality point average of 3.25 overall may also apply to participate in the Dietrich College Senior Honors Programto gain research experience. It is therefore essential to complete this requirement during your junior year at the latest. Each Carnegie Mellon course number begins with a two-digit prefix that designates the department offering the course (i.e., 76-xxx courses are offered by the Department of English). Masters in Computational Data Science at Carnegie Mellon University 2023 - 2024: Check Rankings, Course Fees, Eligibility, Scholarships, Application Deadline for Computational Data Science at Carnegie Mellon University (CMU) at Yocket. 36-200 draws examples from many fields and satisfy the DC College Core Requirement in Statistical Reasoning. **Three years of mathematics should include at least algebra, geometry, trigonometry, analytic geometry, elementary functions as well as pre-calculus. 36-236 is the standard (and recommended) introduction to statistical inference. Average SAT: 1510 The average SAT score composite at Carnegie Mellon is a 1510 on the 1600 SAT scale. The first schedule uses calculus sequence 2. is a rigorous probability theory course offered by the Department of Mathematics. We've got the resources to support you. Youre a scientist. Students come to Carnegie Mellon to learn, create and innovate with the very best. The art lies in knowing which displays or techniques will reveal the most interesting features of a complicated data set. - Defining the product vision . A critical part of statistical practice is understanding the questions being asked so that appropriate methods of analysis can be used. International Applicants College of Fine Arts Applicants To satisfy the Special Topics requirement choose one of the 36-46x courses (which are 9 units). Students who choose to take36-225will be required to take36-226afterward, they will not be eligible to take36-236. Each semester comprises a minimum of 36 units. Bachelor of Science (Jointly offered by the School of Computer Science). 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. The Beginning Data Analysis courses give a hands-on introduction to the art and science of data analysis. ELI BEN-MICHAEL, Assistant Professor (Joint Faculty with Heinz College), ZACHARY BRANSON, Assistant Teaching Professor Ph.D. in Statistics, Harvard University; Carnegie Mellon, 2019, DAVID CHOI, Assistant Professor of Statistics and Information Systems Ph.D., Stanford University; Carnegie Mellon, 2004, ALEXANDRA CHOULDECHOVA, Assistant Professor of Statistics and Public Policy Ph.D. , Stanford University; Carnegie Mellon, 2014, REBECCA DOERGE, Dean of Mellon College of Science, Professor of Statistics PhD, North Carolina State University; Carnegie Mellon, 2016, PETER FREEMAN, Associate Teaching Professor; Director of Undergraduate Studies Ph.D. , University of Chicago; Carnegie Mellon, 2004, MAX G'SELL, Associate Professor Ph.D., Stanford University ; Carnegie Mellon, 2014, CHRISTOPHER R. GENOVESE, Professor of Statistics Ph.D., University of California, Berkeley; Carnegie Mellon, 1994, JOEL B. GREENHOUSE, Professor of Statistics Ph.D., University of Michigan; Carnegie Mellon, 1982, AMELIA HAVILAND, Professor of Statistics and Public Policy Ph.D., Carnegie Mellon University; Carnegie Mellon, 2003, JIASHUN JIN, Professor of Statistics Ph.D., Stanford University; Carnegie Mellon, 2007, BRIAN JUNKER, Professor of Statistics Ph.D., University of Illinois; Carnegie Mellon, 1990, ROBERT E. KASS, Maurice Falk Professor of Statistics & Computational Neuroscience Ph.D., University of Chicago; Carnegie Mellon, 1981, EDWARD KENNEDY, Associate Professor Ph.D., University of Pennsylvania; Carnegie Mellon, 2016, ARUN KUCHIBHOTLA, Assistant Professor PhD, University of Pennsylvania; Carnegie Mellon, 2020, MIKAEL KUUSELA, Assistant Professor PhD, Ecole Polytechnique Federale de Lausanne; Carnegie Mellon, 2018, ANN LEE, Professor, Co-Director of PhD program Ph.D., Brown University; Carnegie Mellon, 2005, JING LEI, Professor Ph.D., University of California, Berkeley; Carnegie Mellon, 2011, ROBIN MEJIA, Assistant Research Professor PhD, UC Berkeley; Carnegie Mellon, 2018, DANIEL NAGIN, Teresa and H. John Heinz III Professor of Public Policy Ph.D., Carnegie Mellon University; Carnegie Mellon, 1976, MATEY NEYKOV, Associate Professor Ph.D., Harvard University; Carnegie Mellon, 2017, NYNKE NIEZINK, Assistant Professor Ph.D., University of Groningen; Carnegie Mellon, 2017, REBECCA NUGENT, Department Head, Stephen E. and Joyce Fienberg Professor of Statistics & Data Science Ph.D., University of Washington; Carnegie Mellon, 2006, AADITYA RAMDAS, Assistant Professor PhD, Carnegie Mellon; Carnegie Mellon, 2018, ALEX REINHART, Assistant Teaching Faculty Ph.D., Carnegie Mellon University; Carnegie Mellon, 2018, ALESSANDRO RINALDO, Associate Dean for Research, Professor Ph.D., Carnegie Mellon; Carnegie Mellon, 2005, KATHRYN ROEDER, UPMC Professor of Statistics and Life Sciences Ph.D., Pennsylvania State University; Carnegie Mellon, 1994, CHAD M. SCHAFER, Professor Ph.D., University of California, Berkeley; Carnegie Mellon, 2004, TEDDY SEIDENFELD, Herbert A. Simon Professor of Philosophy and Statistics Ph.D., Columbia University; Carnegie Mellon, 1985, COSMA SHALIZI, Associate Professor Ph.D., University of Wisconsin, Madison; Carnegie Mellon, 2005, VALERIE VENTURA, Professor, Co-Director of PhD program Ph.D., University of Oxford; Carnegie Mellon, 1997, ISABELLA VERDINELLI, Professor in Residence Ph.D., Carnegie Mellon University; Carnegie Mellon, 1991, LARRY WASSERMAN, UPMC Professor of Statistics Ph.D., University of Toronto; Carnegie Mellon, 1988. The courses cover similar topics but differ slightly in the examples they emphasize. This is a good choice for deepening understanding of statistical ideas and for strengthening research skills. 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. Students graduate in December. It is therefore essential to complete this requirement during your junior year at the latest! Understanding the strengths and weaknesses of various methods allows the data analyst to select the right tool for the job; understanding how they can be adapted to work in new settings greatly extends the realm of problems that he/she can solve. Complete one of the following three courses: *It is recommended that students complete the calculus requirement during their freshman year. Note: Students who enter the program with 36-235 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. 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 (Mathematical Science Track). The following sample program illustrates one way to satisfy the requirements of the Economics and Statistics Major. For all these reasons, Statistics & Data Science students are highly sought-after in the marketplace. If you would like to learn more about this program, please schedule an appointment with Deanna Matthews, Associate Department Head for Undergraduate Affairs.. The Beginning Data Analysis courses give a hands-on introduction to the art and science of data analysis. **The linear algebra requirement needs to be completed before taking 36-401 Modern Regression. 36-200 draws examples from many fields and satisfy the Dietrich College Core Requirement in Statistical Reasoning. While all Majors in Statistics are given solid grounding in computation, extensive computational training is really what sets the Major in Statistics and Machine Learning apart. Please make sure to consult the Undergraduate Statistics Advisor prior to pursuing courses for the concentration area. This program is geared towards students interested in statistical computation, data science, or Big Data problems. Glenn Clune, Academic Program Manager To satisfy the theory requirement take the following two courses: *It is possible to substitute36-218,36-219,36-225, or ). One goal of the Statistics program is to give students experience with statistical research. Test Score Requirements. Students who choose to take36-225instead will be required to take36-226afterward, they will not be eligible to take36-236. 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. Other courses may qualify as well; consult with the Statistics Undergraduate Advisor. Other courses emphasize examples inengineering and architecture (36-220) and the laboratory sciences (36-247). The department gives students research experience through various courses focused on real-world experiences and applications. If students do not have at least three, they need to take additional advanced electives. A technologist. *It is possible to substitute36-218,36-219,36-225 or 21-325 for 36-235. The second schedule is an example of the case when a student enters the program through 36-235 and 36-236 (and therefore skips the beginning data analysis sequence). Statisticians must master diverse skills in computing, mathematics, decision making, forecasting, interpretation of complicated data, and design of meaningful comparisons. These situations may have additional application requirements. ). Additional experience in programming and computational modeling is also recommended. The theory of probability gives a mathematical description of the randomness inherent in our observations. Statistics Majors and Minors seeking substitutions or waivers should speak to the Academic Advisor in Statistics. After completing the common MCDS core courses in the first semester, you can pick from three concentrations: Systems, Analytics, and Human-Centered Data Science. should discuss options with an advisor. 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. Students should discuss this with a Statistics advisor when deciding whether to add an additional major in Statistics. 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. World-renowned for its contributions to statistical theory and practice, the Department of Statistics & Data Science is where imaginatively logical problem-solvers work collaboratively across disciplines, applying statistical tools to real-world challenges. 21-241 and 21-242 are intended only for students with a very strong mathematical background. All economics courses counting towards an economics degree must be completed with a grade of "C" or higher. These courses are usually drawn from a single discipline of interest to the student and must be approved by the Statistics Undergraduate Advisor. Students who elect Statistics as a second or third major must fulfill all Statistics degree requirements except for the Concentration Area requirement. The Bachelor of Science in Statistics and Machine Learning is a program housed in the Department of Statistics & Data Science and is jointly administered with the Department of Machine Learning. The second schedule is an example of the case when a student enters the program through 36-235 and 36-236 (and therefore skips the intermediate data analysis course). The Department of Statistics & Data Science curriculum follows both of these threads and helps the student develop the complementary skills required. for 36-235 Students who maintain a quality point average of 3.25 overall may also apply to participate in the Dietrich College Senior Honors Programfor additional research experience. 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. **All Special Topics are not offered every semester, and new Special Topics are regularly added. An artist. Courses within Statistics can be any 300 or 400 level course (that is not used to satisfy any other requirement for the statistics major). The core objective of our undergraduate program is to provide our students with an education that enables them to be productive, impactful, and fulfilled professionals throughout their careers. (or equivalent) and 36-401. Note that these courses require an application. The Department augments all these strengths with a friendly, energetic working environment and exceptional computing resources. Students in this major are trained to advance the understanding of economic issues through the analysis, synthesis and reporting of data using the advanced empirical research methods of statistics and econometrics. . Where Am I in the Process? Data analysis is the art and science of extracting insight from data. Note: Students who enter the program with 36-235 or 36-236 should discuss options with an advisor. The B.S. *A score of 5 on the Advanced Placement (AP) Exam in Statistics may be used to waive this requirement. To our college counseling partners in high schools and community-based organizations - you're all kinds of amazing. The final authority in such decisions rests there. Students mostly do this through projects in specific courses, such as36-290,36-303, 36-490, 36-493,and/or36-497. (See Dietrich College Interdepartmental Majors as well later in this section). The following is a partial list of courses outside Statistics that qualify as electives as they provide the intellectual infrastructure that will advance the student's understanding of statistics and its applications. In 1967, it became the current-day Carnegie Mellon University through its merger with the Mellon . ) and the laboratory sciences (36-247 These core courses involve extensive analysis of real data with emphasis on developing the oral and writing skills needed for communicating results. Samantha Nielsen, Associate Director of Academic Programs statadvising@stat.cmu.edu. in Statistics (Mathematical Sciences Track), Recommendations for Prospective PhD Students, Additional Major in Statistics (Mathematical Science Track), B.S. The program is geared toward students interested in statistical computation, data science, and "big data" problems. 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. is the standard (and recommended) introduction to probability. Students who elect Statistics and Machine Learning as a second or third major must fulfill all degree requirements. 150-200 word essay describing how the proposed courses complement the Statistics degree. The MCDS program is designed for students with a degree in computer science, computer engineering or a related degree from a highly ranked university. Mar 14 Energy & Environment Improving air quality in Africa 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. Statistics is the science and art of making predictions and decisions in the face of uncertainty. The schedule uses calculus sequence 2, andan advanced data analysis elective (to replace the beginning data analysis course). Mar 6 - Dec 1 Inventing Shakespeare: Text, Technology, and the Four Folios Exhibit. 36-200 draws examples from many fields and satisfies the DC College Core Requirement in Statistical Reasoning. Advanced mathematics courses are encouraged. There are several ongoing exciting research projects in the Department of Statistics & Data Science, and the department enthusiastically seeks to involve undergraduates in this work. In addition this number includes the 36 units of the Concentration Area category which may not be required (see category 7 above for details). In light of this vision, the objectives of the Bachelor of Science in Mechanical Engineering at Carnegie Mellon are to produce graduates who: 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. **It is possible to substitute36-226or36-326(honors course) for36-236. is a rigorous Probability Theory course offered by the Department of Mathematics.) (i) In order to meet the prerequisite requirements, a grade of at least a C is required in36-235 assessment test if an acceptable alternative to completing, *The Beginning and Intermediate Data Analysis sequence (i.e. 36-236is the standard introduction to statistical inference. Students are advised to begin planning their curriculum (with appropriate advisors) as soon as possible. Data provided by researchers at Carnegie Mellon University and Texas A&M University. 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). For deepening understanding of statistical ideas and for strengthening research skills additional major in another Department College! And applications highly sought-after in the marketplace is not an exhaustive list, such as36-290,36-303, 36-490 36-493. Must complement the overall Statistics degree requirements and applications choose to take36-225instead be! Support other possible schedules ( see Dietrich College Core requirement in statistical computation, science. Primary ) major in another Department or College introduction to carnegie mellon university data science requirements art and science of extracting insight data. 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