Statistics Major
Paul H. Chook Department of Statistics and Computer Information Systems
Department of Mathematics
Statistical methods are crucial in numerous fields such as biology, physics, climate science, and finance, to name a few. The Bachelor of Arts in Statistics major is intended to provide students with fundamental knowledge and skills in probability, mathematical statistics, data analysis, and statistical computing. Students will explore the mathematical foundations of the theory of statistics. The demand for these skills has increased with the rise of big data. This major is intended to prepare students for graduate study in statistics or related subjects or for a career in data analysis or other related fields.
A student majoring in statistics cannot minor in mathematics; nor can they declare a second major in actuarial science, financial mathematics, or mathematics.
Please note – Any business courses completed for this major (CIS, OPR, STA) do not count toward the 90 liberal arts credit minimum for the BA degree.
Requirements for the Major
| Program Prerequisites: | ||
| Students must satisfy the following: | ||
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| As a preliminary requirement, students must complete the following courses: | ||
| STA 2000 |
Business Statistics I | 3 credits |
| Students must complete the calculus prerequisite, which may be achieved by either of the following two options: | ||
| Option 1 | MTH 2600 Calculus I with Trigonometry Refresher or MTH 2610 Calculus I
And MTH 3010 Calculus II And MTH 3020 Calculus III or MTH 3050 Calculus III and Vector Calculus * |
12 credits |
| or | ||
| Option 2 | One of the following:
MTH 2205 Precalculus and Elements of Calculus 1B MTH 2206 Applied Calculus MTH 2207 Elements of Calculus I and Matrix Applications And MTH 3006 Elements of Calculus II And MTH 3030 Elements of Calculus III |
12-13 credits |
| * MTH 3050 is not open to students who completed MTH 3020, MTH 3030, MTH 3035, or their equivalent. | ||
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A First Course in Linear Algebra or Linear Algebra and Matrix Methods |
3 credits |
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Introduction to Probability** |
4 credits |
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Mathematics of Inferential Statistics |
4 credits |
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Statistical Computing |
3 credits |
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Data Mining and Statistical Learning (formerly Data Mining for Business Analytics) |
3 credits |
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STA 4155 * |
Regression and Forecasting Models for Business Applications |
3 credits |
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or |
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MTH 4130 * |
Mathematics of Data Analysis |
4 credits |
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NOTES: * Students can receive credit for only one of these two courses. |
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Students must take one of the following courses: *** |
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Machine Learning and Artificial Intelligence |
3 credits |
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Analysis of Time Series |
3 credits |
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Experimental Design for Machine Learning |
3 credits |
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Quantitative Decision Making for Business I |
3 credits |
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*** These courses may also be used as electives for the major |
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Electives Students must complete one additional course from the following list: |
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Bridge to Higher Mathematics |
3 credits |
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Mathematical Analysis I |
3 credit |
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Advanced Calculus II |
3 credits |
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Topology |
3 credits |
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Ordinary Differential Equations |
3 credits |
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Numerical Methods for Differential Equations in Finance |
4 credits |
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Introduction to Stochastic Process |
4 credits |
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Computational Methods in Probability |
3 credits |
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Graph Theory |
3 credits |
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Mathematical Modeling * |
3 credits |
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Combinatorics |
3 credits |
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Theory of Numbers |
3 credits |
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Elements of Modern Algebra |
3 credits |
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Introduction to Modern Geometry |
3 credits |
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History of Mathematics |
3 credits |
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Differential Geometry * |
3 credits |
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Algorithms, Computers and Programming II |
3 credits |
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Methods of Numerical Analysis |
3 credits |
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Introduction to Mathematical Logic |
3 credits |
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Data Structures and Algorithms (formerly Fundamental Algorithms) |
3 credits |
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Theory of Interest |
3 credits |
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Actuarial Mathematics I |
4 credits |
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Actuarial Mathematics II |
4 credits |
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Short-Term Insurance Mathematics |
4 credits |
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Introductory Financial Mathematics |
4 credits |
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Data Analysis and Simulation for Financial Engineers |
4 credits |
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Advanced Calculus III * |
3 credits |
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Theory of Functions of a Complex Variable |
3 credits |
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Theory of Functions of Real Variables * |
3 credits |
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Partial Differential Equations and Boundary Value Problems * |
4 credits |
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Stochastic Calculus for Finance |
4 credits |
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Programming and Computational Thinking |
3 credits |
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Object-Oriented Programming |
3 credits |
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Programming for Analytics |
3 credits |
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Database Management Systems I |
3 credits |
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Object-Oriented Programming II |
3 credits |
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Data Warehousing for Analytics |
3 credits |
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Quantitative Decision Making for Business I |
3 credits |
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Quantitative Decision Making for Business II |
3 credits |
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Bayesian Statistical Inference and Decision Making |
3 credits |
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Special Topics in Operations Research |
3 credits |
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Independent Study and Research in Operations Research |
3 credits |
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Introduction to SAS Programming |
3 credits |
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Experimental Design for Machine Learning (formerly Design and Analysis of Experimental Data) |
3 credits |
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Analysis of Time Series |
3 credits |
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Data Visualization |
3 credits |
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Special Topics in Applied Statistics |
3 credits |
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Machine Learning and Artificial Intelligence |
3 credits |
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Independent Study in Statistics |
3 credits |
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* These courses are offered infrequently, subject to student demand. |
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Students are expected to complete the major requirements in place at the time they are officially accepted into their programs. Please review the College Bulletin for the relevant academic year.
Contact
Professor Youngdeok Hwang
Department of Statistics and Computer Information Systems, 646 312-3411