Applied Statistics and Data Analytics Bachelor of Science Degree
Applied Statistics and Data Analytics
Bachelor of Science Degree
Using statistics, probability, and computing, statisticians apply their knowledge of statistical methods—from data collection, and processing, through analysis and interpretation—to a variety of areas, including biology, economics, engineering, manufacturing, medicine, public health, psychology, marketing, and sports.
47%
Job postings that require skills in statistical software like SAS or R
34%
Employment growth expected for statisticians by 2026, four times faster than the overall labor market
#1
Ranking for Statisticians in Best Business Jobs List, U.S. News & World Report, 2020
Overview for Applied Statistics and Data Analytics BS
- Recent graduates are employed at Freehold Capital Management, Qool Media, Excellus BlueCross BlueShield, 3M, and General Electric.
- Join the PiRIT, a student club that fosters a community of students and faculty in mathematics and statistics who share the goal of enriching student understanding of the broad range of mathematics beyond the classroom.
The applied statistics and data analytics degree provides you with a strong foundation in statistical methodology, experience in its applications, a solid background in the use of statistical computing packages, and the skills to collaborate on projects that rely on statistical analysis. The degree gives you an advantage in the fields of business, government, and industry, and also prepares you for advanced study in graduate programs. Diverse application areas for graduates include product design, biostatistics, data analytics, quality control, and statistical forecasting.
Educational Approach
Early courses are designed to give you a foundation in calculus, statistics, algebra, and computer science. Application areas are very diverse and include product design, biostatistics, actuarial science, quality control, and statistical forecasting.
Real-World Experiences
Students collaborate with specialists in both scientific and non-technical areas to design and conduct experiments and interpret the results. Application areas are very diverse and include product design, biostatistics, actuarial science, quality control, and statistical forecasting.
Nature of Work
Statisticians contribute to scientific inquiry by applying their mathematical and statistical knowledge to the design of surveys and experiments; collection, processing, and analysis of data; and interpretation of the results. Statisticians may apply their knowledge of statistical methods to a variety of subject areas, such as biology, economics, engineering, medicine, public health, psychology, marketing, education, and sports. Many economic, social, political, and military decisions cannot be made without the use of statistical techniques, such as the design of experiments to gain federal approval of a newly manufactured drug. In industry, statisticians play an important role in quality control and product/process improvement based on data analysis.
Advanced Degrees
Graduate programs offered by the School of Mathematics and Statistics introduce students to rigorous advanced applied mathematical and statistical methodology. Students realize the potential for that cutting-edge methodology as a general tool in the study of exciting problems in science, business, and industry. The school offers the following advanced degrees: an advanced certificate in applied statistics, master of science degrees in applied and computational mathematics and applied statistics, and a doctorate degree in mathematical modeling.
Combined Accelerated Bachelor’s/Master’s Degrees
Today’s careers require advanced degrees grounded in real-world experience. RIT’s Combined Accelerated Bachelor’s/Master’s Degrees enable you to earn both a bachelor’s and a master’s degree in as little as five years of study, all while gaining the valuable hands-on experience that comes from co-ops, internships, research, study abroad, and more.
+1 MBA: Students who enroll in a qualifying undergraduate degree have the opportunity to add an MBA to their bachelor’s degree after their first year of study, depending on their program. Learn how the +1 MBA can accelerate your learning and position you for success.
Meet us on campus
Learn about academics, co-op and internships, financial aid, and more.
Careers and Cooperative Education
Typical Job Titles
| Statistician | Biostatistician |
| Data Scientist | Quantitative Analyst |
| Data Engineer | Business Analytics Associate |
| Quality Analyst | Research Analyst |
| Reporting and Data Analytics Specialist |
Industries
Salary and Career Information for Applied Statistics and Data Analytics BS
Cooperative Education
What’s different about an RIT education? It’s the career experience you gain by completing cooperative education and internships with top companies in every single industry. You’ll earn more than a degree. You’ll gain real-world career experience that sets you apart. It’s exposure–early and often–to a variety of professional work environments, career paths, and industries.
Co-ops and internships take your knowledge and turn it into know-how. Experiential learning opportunities in statistics include a range of hands-on experiences, from co-ops and internships to undergraduate research that enable you to apply your statistical knowledge in professional settings while you make valuable connections between classwork and real-world applications.
Featured Profiles
The Power of Being Data Literate in a Data-Driven World
Melissa Royo ‘09/’10 (applied statistics)
The applied nature of the statistics programs at RIT helped Melissa Royo ’09/’10 get a sense for how real-world data behaves.
Your Partners in Success: Meet Our Faculty, Dr. Wong
Dr. Tony Wong
Mathematics is a powerful tool for answering questions. From mitigating climate risks to splitting the dinner bill, Professor Wong shows students that math is more than just a prerequisite.
Curriculum for 2023-2024 for Applied Statistics and Data Analytics BS
Current Students: See Curriculum Requirements
Applied Statistics and Data Analytics, BS degree, typical course sequence
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| First Year | ||
| ISCH-110 | Principles of Computing (General Education) This course is designed to introduce students to the central ideas of computing. Students will engage in activities that show how computing changes the world and impacts daily lives. Students will develop step-by-step written solutions to basic problems and implement their solutions using a programming language. Assignments will be completed both individually and in small teams. Students will be required to demonstrate oral and written communication skills through such assignments as short papers, homework, group discussions and debates, and development of a term paper. Computer Science majors may take this course only with department approval, and may not apply these credits toward their degree requirements. Lec/Lab 3 (Fall, Spring). |
3 |
| MATH-181 | Calculus I (General Education – Mathematical Perspective A) This is the first in a two-course sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals. (Prerequisites: MATH-111 or (NMTH-220 and NMTH-260 or NMTH-272 or NMTH-275) or equivalent courses with a minimum grade of B-, or a score of at least 60% on the RIT Mathematics Placement Exam.
Co-requisites: MATH-181R or equivalent course.) Lecture 6 (Fall, Spring). |
4 |
| MATH-182 | Calculus II (General Education – Mathematical Perspective B) This is the second in a two-course sequence. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates. (Prerequisites: C- or better in MATH-181 or MATH-181A or equivalent course.) Lecture 6 (Fall, Spring). |
4 |
| MATH-199 | Mathematics and Statistics Seminar This course introduces the programs within the School of Mathematical Sciences, and provides an introduction to math and statistics software. The course provides practice in technical writing. Seminar 1 (Fall). |
1 |
| YOPS-10 | RIT 365: RIT Connections RIT 365 students participate in experiential learning opportunities designed to launch them into their career at RIT, support them in making multiple and varied connections across the university, and immerse them in processes of competency development. Students will plan for and reflect on their first-year experiences, receive feedback, and develop a personal plan for future action in order to develop foundational self-awareness and recognize broad-based professional competencies. (This class is restricted to incoming 1st year or global campus students.) Lecture 1 (Fall, Spring). |
0 |
General Education – Elective |
3 | |
General Education – First-Year Writing (WI) |
3 | |
General Education – Ethical Perspective |
3 | |
General Education – Artistic Perspective |
3 | |
General Education – Natural Science Inquiry Perspective† |
4 | |
| Second Year | ||
| MATH-200 | Discrete Mathematics and Introduction to Proofs This course prepares students for professions that use mathematics in daily practice, and for mathematics courses beyond the introductory level where it is essential to communicate effectively in the language of mathematics. It covers various methods of mathematical proof, starting with basic techniques in propositional and predicate calculus and set theory, and then moving to applications in advanced mathematics. (Prerequisite: MATH-173 or MATH-182 or MATH-182A or equivalent course.) Lecture 3, Recitation 4 (Fall). |
3 |
| MATH-251 | Probability and Statistics This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to real-world problems. A statistical package such as Minitab or R is used for data analysis and statistical applications. (Prerequisites: MATH-173 or MATH-182 or MATH 182A or equivalent course.) Lecture 3, Recitation 1 (Fall, Spring, Summer). |
3 |
| STAT-257 | Statistical Inference Learn how data furthers understanding of science and engineering. This course covers basic statistical concepts, sampling theory, hypothesis testing, confidence intervals, point estimation, and simple linear regression. A statistical software package such as MINITAB will be used for data analysis and statistical applications. (Prerequisites: MATH-251.
NOTE: Students cannot receive credit for both MATH-252 and STAT-257 nor for both STAT-205 and STAT-257.) Lecture 3 (Fall, Spring). |
3 |
| MATH-399 | Mathematical Sciences Job Search Seminar This course helps students prepare to search for co-op or full-time employment. Students will learn strategies for conducting a successful job search and transitioning into the work world. The course meets one hour each week for five weeks. Lecture 1 (Fall, Spring). |
0 |
| Choose one of the following: | 4 |
|
| MATH-221 | Multivariable and Vector Calculus (General Education) This course is principally a study of the calculus of functions of two or more variables, but also includes a study of vectors, vector-valued functions and their derivatives. The course covers limits, partial derivatives, multiple integrals, Stokes' Theorem, Green's Theorem, the Divergence Theorem, and applications in physics. Credit cannot be granted for both this course and MATH-219. (Prerequisite: C- or better MATH-173 or MATH-182 or MATH-182A or equivalent course.) Lecture 4 (Fall, Spring, Summer). |
|
| MATH-221H | Honors Multivariable and Vector Calculus (General Education) |
|
| Choose one of the following: | 3 |
|
| MATH-241 | Linear Algebra This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course. (Prerequisites: MATH-190 or MATH-200 or MATH-219 or MATH-220 or MATH-221 or MATH-221H or equivalent course.) Lecture 3 (Fall, Spring). |
|
| MATH-241H | Honors Linear Algebra |
|
Open Elective |
3 | |
General Education – Elective |
3 | |
General Education – Global Perspective |
3 | |
General Education – Social Perspective |
3 | |
General Education – Scientific Principles Perspective† |
4 | |
| Third Year | ||
| STAT-305 | Regression Analysis This course covers regression techniques with applications to the type of problems encountered in real-world situations. It includes use of the statistical software SAS. Topics include a review of simple linear regression, residual analysis, multiple regression, matrix approach to regression, model selection procedures, and various other models as time permits. (Prerequisites: MATH-241 and (MATH-252 or STAT-257) or equivalent courses.) Lecture 3 (Spring). |
3 |
| STAT-325 | Design of Experiments (WI-PR) This course is a study of the design and analysis of experiments. It includes extensive use of statistical software. Topics include single-factor analysis of variance, multiple comparisons and model validation, multifactor factorial designs, fixed, random and mixed models, expected mean square calculations, confounding, randomized block designs, and other designs and topics as time permits. (Prerequisites: STAT-205 or MATH-252 or STAT-257 or equivalent courses.) Lecture 3 (Fall). |
3 |
Program Electives‡ |
15 | |
General Education – Immersion 1, 2 |
6 | |
General Education – Elective |
3 | |
| Fourth Year | ||
| STAT-405 | Mathematical Statistics I This course provides a brief review of basic probability concepts and distribution theory. It covers mathematical properties of distributions needed for statistical inference. (Prerequisites: STAT-205 or MATH-252 or STAT-257 or equivalent courses.) Lecture 3 (Fall). |
3 |
| STAT-406 | Mathematical Statistics II This course is a continuation of STAT-405 covering classical and Bayesian methods in estimation theory, chi-square test, Neyman-Pearson lemma, mathematical justification of standard test procedures, sufficient statistics, and further topics in statistical inference. (Prerequisites: STAT-405 or equivalent course.) Lecture 3 (Spring). |
3 |
| STAT-500 | Senior Capstone in Statistics (WI-PR) This course introduces the student to statistical situations not encountered in regular course of study. It integrates and synthesizes concepts in statistical theory with applications. Topics include open-ended analysis of data, current techniques and practice of statistics, development of statistical communication skills and the use of statistical software tools in data analysis. Each student is required to learn and use a statistical technique beyond what is covered in the previous courses. Students are expected to introduce the method in a presentation and to prepare a comprehensive, professional report detailing the statistical method and its application to a data set. (Corequisites: STAT-305 and STAT-325 or equivalent courses.) Lecture 3 (Spring). |
3 |
| STAT-501 | Experiential Learning Requirement in Statistics The experiential learning (EL) requirement may be fulfilled through a variety of methods including capstone, co-op, undergraduate research, summer research experiences, study abroad relevant to the major, designated EL courses, etc. All experiences must be approved by the School of Mathematical Sciences. Successful completion of the required elements will result in a grade of S in this course. Lecture (Fall, Spring, Summer). |
0 |
General Education – Immersion 3 |
3 | |
Program Electives‡ |
3 | |
Open Electives |
9 | |
General Education – Electives |
6 | |
| Total Semester Credit Hours | 120 |
|
Please see General Education Curriculum (GE) for more information.
(WI) Refers to a writing intensive course within the major.
* Please see Wellness Education Requirement for more information. Students completing bachelor's degrees are required to complete two different Wellness courses.
† Students will satisfy this requirement by taking either University Physics I (PHYS-211) and University Physics II (PHYS-212) or General & Analytical Chemistry I and Lab (CHMG-141/145) and General & Analytical Chemistry II and Lab (CHMG-142/146) or General Biology I and Lab (BIOL-101/103) and General Biology II and Lab (BIOL-102/104).
‡ Three of the six program electives must be from the following list of courses: Actuarial Mathematics (MATH-255), Topics in Mathematics of Finance (MATH-261), Stochastic Processes (MATH-505), Introduction to Time Series (STAT-335), Nonparametric Statistics (STAT-345), Multivariate Analysis (STAT-425), Statistical Software - R (STAT-511), Statistical Quality Control (STAT-521), Data Mining (STAT-547), Survey Design and Analysis (STAT-572), Categorical Data Analysis (STAT-584). A program elective is any MATH or STAT course with a course number higher than 250.
Up to 2 program electives can be selected from the following list: Financial Accounting (ACCT-110), Data Literacy Analytics & Decision Making (BANA-255), Statistical Analysis for Bioinformatics (BIOL-470), Operations Management (DECS-310), Econometrics I (ECON-403), Financial Management (FINC-220), Financial Analytics (FINC-580), Lean Six Sigma Fundamentals ISEE-582), Marketing Analytics (MKTG-365)
Combined Accelerated Bachelor's/Master's Degrees
The curriculum below outlines the typical course sequence(s) for combined accelerated degrees available with this bachelor's degree.
Applied Statistics and Data Analytics, BS degree/Applied and Computational Mathematics (thesis option), MS degree, typical course sequence
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| First Year | ||
| ISCH-110 | Principles of Computing This course is designed to introduce students to the central ideas of computing. Students will engage in activities that show how computing changes the world and impacts daily lives. Students will develop step-by-step written solutions to basic problems and implement their solutions using a programming language. Assignments will be completed both individually and in small teams. Students will be required to demonstrate oral and written communication skills through such assignments as short papers, homework, group discussions and debates, and development of a term paper. Computer Science majors may take this course only with department approval, and may not apply these credits toward their degree requirements. Lec/Lab 3 (Fall, Spring). |
3 |
| MATH-181 | General Education - Mathematical Perspective A: Project-Based Calculus I This is the first in a two-course sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals. (Prerequisites: MATH-111 or (NMTH-220 and NMTH-260 or NMTH-272 or NMTH-275) or equivalent courses with a minimum grade of B-, or a score of at least 60% on the RIT Mathematics Placement Exam.
Co-requisites: MATH-181R or equivalent course.) Lecture 6 (Fall, Spring). |
4 |
| MATH-182 | General Education - Mathematical Perspective B: Project-Based Calculus II This is the second in a two-course sequence. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates. (Prerequisites: C- or better in MATH-181 or MATH-181A or equivalent course.) Lecture 6 (Fall, Spring). |
4 |
| MATH-199 | Mathematics and Statistics Seminar This course introduces the programs within the School of Mathematical Sciences, and provides an introduction to math and statistics software. The course provides practice in technical writing. Seminar 1 (Fall). |
1 |
| YOPS-10 | RIT 365: RIT Connections RIT 365 students participate in experiential learning opportunities designed to launch them into their career at RIT, support them in making multiple and varied connections across the university, and immerse them in processes of competency development. Students will plan for and reflect on their first-year experiences, receive feedback, and develop a personal plan for future action in order to develop foundational self-awareness and recognize broad-based professional competencies. (This class is restricted to incoming 1st year or global campus students.) Lecture 1 (Fall, Spring). |
0 |
General Education - Elective |
3 | |
General Education - First Year Writing (WI) |
3 | |
General Education - Ethical Perspective |
3 | |
General Education - Artistic Perspective |
3 | |
General Education - Natural Science Inquiry Perspective† |
4 | |
General Education - Scientific Principles Perspective† |
4 | |
| Second Year | ||
| MATH-200 | Discrete Mathematics and Introduction to Proofs This course prepares students for professions that use mathematics in daily practice, and for mathematics courses beyond the introductory level where it is essential to communicate effectively in the language of mathematics. It covers various methods of mathematical proof, starting with basic techniques in propositional and predicate calculus and set theory, and then moving to applications in advanced mathematics. (Prerequisite: MATH-173 or MATH-182 or MATH-182A or equivalent course.) Lecture 3, Recitation 4 (Fall). |
3 |
| MATH-231 | Differential Equations This course is an introduction to the study of ordinary differential equations and their applications. Topics include solutions to first order equations and linear second order equations, method of undetermined coefficients, variation of parameters, linear independence and the Wronskian, vibrating systems, and Laplace transforms. (Prerequisite: MATH-173 or MATH-182 or MATH-182A or equivalent course.) Lecture 3, Recitation 1 (Fall, Spring, Summer). |
3 |
| MATH-251 | Probability and Statistics This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to real-world problems. A statistical package such as Minitab or R is used for data analysis and statistical applications. (Prerequisites: MATH-173 or MATH-182 or MATH 182A or equivalent course.) Lecture 3, Recitation 1 (Fall, Spring, Summer). |
3 |
| MATH-399 | Mathematical Science Job Search Seminar This course helps students prepare to search for co-op or full-time employment. Students will learn strategies for conducting a successful job search and transitioning into the work world. The course meets one hour each week for five weeks. Lecture 1 (Fall, Spring). |
0 |
| Choose one of the following: | 4 |
|
| MATH-221 | Multivariable and Vector Calculus This course is principally a study of the calculus of functions of two or more variables, but also includes a study of vectors, vector-valued functions and their derivatives. The course covers limits, partial derivatives, multiple integrals, Stokes' Theorem, Green's Theorem, the Divergence Theorem, and applications in physics. Credit cannot be granted for both this course and MATH-219. (Prerequisite: C- or better MATH-173 or MATH-182 or MATH-182A or equivalent course.) Lecture 4 (Fall, Spring, Summer). |
|
| MATH-221H | Honors Multivariable and Vector Calculus |
|
| Choose one of the following: | 3 |
|
| MATH-241 | Linear Algebra This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course. (Prerequisites: MATH-190 or MATH-200 or MATH-219 or MATH-220 or MATH-221 or MATH-221H or equivalent course.) Lecture 3 (Fall, Spring). |
|
| MATH-241H | Honors Linear Algebra |
|
| STAT-257 | Statistical Inference Learn how data furthers understanding of science and engineering. This course covers basic statistical concepts, sampling theory, hypothesis testing, confidence intervals, point estimation, and simple linear regression. A statistical software package such as MINITAB will be used for data analysis and statistical applications. (Prerequisites: MATH-251.
NOTE: Students cannot receive credit for both MATH-252 and STAT-257 nor for both STAT-205 and STAT-257.) Lecture 3 (Fall, Spring). |
3 |
General Education - Immersion 1, 2 |
6 | |
General Education - Global Perspective |
3 | |
General Education - Social Perspective |
3 | |
| Third Year | ||
| STAT-305 | Regression Analysis This course covers regression techniques with applications to the type of problems encountered in real-world situations. It includes use of the statistical software SAS. Topics include a review of simple linear regression, residual analysis, multiple regression, matrix approach to regression, model selection procedures, and various other models as time permits. (Prerequisites: MATH-241 and (MATH-252 or STAT-257) or equivalent courses.) Lecture 3 (Spring). |
3 |
| STAT-325 | Design of Experiments (WI-PR) This course is a study of the design and analysis of experiments. It includes extensive use of statistical software. Topics include single-factor analysis of variance, multiple comparisons and model validation, multifactor factorial designs, fixed, random and mixed models, expected mean square calculations, confounding, randomized block designs, and other designs and topics as time permits. (Prerequisites: STAT-205 or MATH-252 or STAT-257 or equivalent courses.) Lecture 3 (Fall). |
3 |
Open Electives |
9 | |
General Education - Immersion 3 |
3 | |
Program Electives‡ |
12 | |
| Fourth Year | ||
| MATH-606 | Graduate Seminar I The course prepares students to engage in activities necessary for independent mathematical research and introduces students to a broad range of active interdisciplinary programs related to applied mathematics. (This course is restricted to students in the ACMTH-MS or MATHML-PHD programs.) Lecture 2 (Fall). |
1 |
| MATH-607 | Graduate Seminar II This course is a continuation of Graduate Seminar I. It prepares students to engage in activities necessary for independent mathematical research and introduces them to a broad range of active interdisciplinary programs related to applied mathematics. (Prerequisite: MATH-606 or equivalent course or students in the ACMTH-MS or MATHML-PHD programs.) Lecture 2 (Spring). |
1 |
| STAT-405 | Mathematical Statistics I This course provides a brief review of basic probability concepts and distribution theory. It covers mathematical properties of distributions needed for statistical inference. (Prerequisites: STAT-205 or MATH-252 or STAT-257 or equivalent courses.) Lecture 3 (Fall). |
3 |
| STAT-406 | Mathematical Statistics II This course is a continuation of STAT-405 covering classical and Bayesian methods in estimation theory, chi-square test, Neyman-Pearson lemma, mathematical justification of standard test procedures, sufficient statistics, and further topics in statistical inference. (Prerequisites: STAT-405 or equivalent course.) Lecture 3 (Spring). |
3 |
| STAT-500 | Senior Capstone in Statistics (WI-PR) This course introduces the student to statistical situations not encountered in regular course of study. It integrates and synthesizes concepts in statistical theory with applications. Topics include open-ended analysis of data, current techniques and practice of statistics, development of statistical communication skills and the use of statistical software tools in data analysis. Each student is required to learn and use a statistical technique beyond what is covered in the previous courses. Students are expected to introduce the method in a presentation and to prepare a comprehensive, professional report detailing the statistical method and its application to a data set. (Corequisites: STAT-305 and STAT-325 or equivalent courses.) Lecture 3 (Spring). |
3 |
| STAT-501 | Experiential Learning Requirement in Statistics The experiential learning (EL) requirement may be fulfilled through a variety of methods including capstone, co-op, undergraduate research, summer research experiences, study abroad relevant to the major, designated EL courses, etc. All experiences must be approved by the School of Mathematical Sciences. Successful completion of the required elements will result in a grade of S in this course. Lecture (Fall, Spring, Summer). |
0 |
Math Graduate Core Courses |
9 | |
General Education - Electives |
9 | |
Open Elective |
3 | |
| Fifth Year | ||
| MATH-790 | Research & Thesis Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor. (This course is restricted to students in the ACMTH-MS or MATHML-PHD programs.) Thesis (Fall, Spring, Summer). |
7 |
Math Graduate Electives |
12 | |
| Total Semester Credit Hours | 144 |
|
Please see General Education Curriculum for more information.
(WI) Refers to a writing intensive course within the major.
* Please see Wellness Education Requirement for more information. Students completing bachelor's degrees are required to complete two different Wellness courses.
† Students will satisfy this requirement by taking either University Physics I (PHYS-211) and University Physics II (PHYS-212) or General & Analytical Chemistry I and Lab (CHMG-141/145) and General & Analytical Chemistry II and Lab (CHMG-142/146) or General Biology I and Lab (BIOL-101/103) and General Biology II and Lab (BIOL-102/104).
‡ The four program electives must be from the following list of courses: Actuarial Mathematics (MATH-255), Topics in Mathematics of Finance (MATH-261), Stochastic Processes (MATH-505), Introduction to Time Series (STAT-335), Nonparametric Statistics (STAT-345), Multivariate Analysis (STAT-425), Statistical Software - R (STAT-511), Statistical Quality Control (STAT-521), Data Mining (STAT-547), Survey Design and Analysis (STAT-572), Categorical Data Analysis (STAT-584). A program elective is any MATH or STAT course with a course number higher than 250.
Applied Statistics and Data Analytics, BS degree/Applied and Computational Mathematics (project option), MS degree, typical course sequence
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| First Year | ||
| ISCH-110 | Principles of Computing This course is designed to introduce students to the central ideas of computing. Students will engage in activities that show how computing changes the world and impacts daily lives. Students will develop step-by-step written solutions to basic problems and implement their solutions using a programming language. Assignments will be completed both individually and in small teams. Students will be required to demonstrate oral and written communication skills through such assignments as short papers, homework, group discussions and debates, and development of a term paper. Computer Science majors may take this course only with department approval, and may not apply these credits toward their degree requirements. Lec/Lab 3 (Fall, Spring). |
3 |
| MATH-181 | General Education - Mathematical Perspective A: Project-Based Calculus I This is the first in a two-course sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals. (Prerequisites: MATH-111 or (NMTH-220 and NMTH-260 or NMTH-272 or NMTH-275) or equivalent courses with a minimum grade of B-, or a score of at least 60% on the RIT Mathematics Placement Exam.
Co-requisites: MATH-181R or equivalent course.) Lecture 6 (Fall, Spring). |
4 |
| MATH-182 | General Education - Mathematical Perspective B: Project-Based Calculus II This is the second in a two-course sequence. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates. (Prerequisites: C- or better in MATH-181 or MATH-181A or equivalent course.) Lecture 6 (Fall, Spring). |
4 |
| MATH-199 | Mathematics and Statistics Seminar This course introduces the programs within the School of Mathematical Sciences, and provides an introduction to math and statistics software. The course provides practice in technical writing. Seminar 1 (Fall). |
1 |
| YOPS-10 | RIT 365: RIT Connections RIT 365 students participate in experiential learning opportunities designed to launch them into their career at RIT, support them in making multiple and varied connections across the university, and immerse them in processes of competency development. Students will plan for and reflect on their first-year experiences, receive feedback, and develop a personal plan for future action in order to develop foundational self-awareness and recognize broad-based professional competencies. (This class is restricted to incoming 1st year or global campus students.) Lecture 1 (Fall, Spring). |
0 |
General Education - Elective |
3 | |
General Education - First Year Writing (WI) |
3 | |
General Education - Artistic Perspective |
3 | |
General Education - Ethical Perspective |
3 | |
General Education - Natural Science Inquiry Perspective† |
4 | |
General Education - Scientific Principles Perspective† |
4 | |
| Second Year | ||
| MATH-200 | Discrete Mathematics and Introduction to Proofs This course prepares students for professions that use mathematics in daily practice, and for mathematics courses beyond the introductory level where it is essential to communicate effectively in the language of mathematics. It covers various methods of mathematical proof, starting with basic techniques in propositional and predicate calculus and set theory, and then moving to applications in advanced mathematics. (Prerequisite: MATH-173 or MATH-182 or MATH-182A or equivalent course.) Lecture 3, Recitation 4 (Fall). |
3 |
| Choose one of the following: | 4 |
|
| MATH-221 | Multivariable and Vector Calculus This course is principally a study of the calculus of functions of two or more variables, but also includes a study of vectors, vector-valued functions and their derivatives. The course covers limits, partial derivatives, multiple integrals, Stokes' Theorem, Green's Theorem, the Divergence Theorem, and applications in physics. Credit cannot be granted for both this course and MATH-219. (Prerequisite: C- or better MATH-173 or MATH-182 or MATH-182A or equivalent course.) Lecture 4 (Fall, Spring, Summer). |
|
| MATH-221H | Honors Multivariable and Vector Calculus |
|
| MATH-231 | Differential Equations This course is an introduction to the study of ordinary differential equations and their applications. Topics include solutions to first order equations and linear second order equations, method of undetermined coefficients, variation of parameters, linear independence and the Wronskian, vibrating systems, and Laplace transforms. (Prerequisite: MATH-173 or MATH-182 or MATH-182A or equivalent course.) Lecture 3, Recitation 1 (Fall, Spring, Summer). |
3 |
| Choose one of the following: | 3 |
|
| MATH-241 | Linear Algebra This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course. (Prerequisites: MATH-190 or MATH-200 or MATH-219 or MATH-220 or MATH-221 or MATH-221H or equivalent course.) Lecture 3 (Fall, Spring). |
|
| MATH-241H | Honor Linear Algebra |
|
| MATH-251 | Probability and Statistics I This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to real-world problems. A statistical package such as Minitab or R is used for data analysis and statistical applications. (Prerequisites: MATH-173 or MATH-182 or MATH 182A or equivalent course.) Lecture 3, Recitation 1 (Fall, Spring, Summer). |
3 |
| MATH-399 | Mathematical Science Job Search Seminar This course helps students prepare to search for co-op or full-time employment. Students will learn strategies for conducting a successful job search and transitioning into the work world. The course meets one hour each week for five weeks. Lecture 1 (Fall, Spring). |
0 |
| STAT-257 | Statistical Inference Learn how data furthers understanding of science and engineering. This course covers basic statistical concepts, sampling theory, hypothesis testing, confidence intervals, point estimation, and simple linear regression. A statistical software package such as MINITAB will be used for data analysis and statistical applications. (Prerequisites: MATH-251.
NOTE: Students cannot receive credit for both MATH-252 and STAT-257 nor for both STAT-205 and STAT-257.) Lecture 3 (Fall, Spring). |
3 |
General Education - Immersion 1, 2 |
6 | |
General Education - Global Perspective |
3 | |
General Education - Social Perspective |
3 | |
| Third Year | ||
| STAT-305 | Regression Analysis This course covers regression techniques with applications to the type of problems encountered in real-world situations. It includes use of the statistical software SAS. Topics include a review of simple linear regression, residual analysis, multiple regression, matrix approach to regression, model selection procedures, and various other models as time permits. (Prerequisites: MATH-241 and (MATH-252 or STAT-257) or equivalent courses.) Lecture 3 (Spring). |
3 |
| STAT-325 | Design of Experiments (WI-PR) This course is a study of the design and analysis of experiments. It includes extensive use of statistical software. Topics include single-factor analysis of variance, multiple comparisons and model validation, multifactor factorial designs, fixed, random and mixed models, expected mean square calculations, confounding, randomized block designs, and other designs and topics as time permits. (Prerequisites: STAT-205 or MATH-252 or STAT-257 or equivalent courses.) Lecture 3 (Fall). |
3 |
Open Electives |
9 | |
General Education - Immersion 3 |
3 | |
Program Electives‡ |
12 | |
| Fourth Year | ||
| MATH-606 | Graduate Seminar I The course prepares students to engage in activities necessary for independent mathematical research and introduces students to a broad range of active interdisciplinary programs related to applied mathematics. (This course is restricted to students in the ACMTH-MS or MATHML-PHD programs.) Lecture 2 (Fall). |
1 |
| MATH-607 | Graduate Seminar II This course is a continuation of Graduate Seminar I. It prepares students to engage in activities necessary for independent mathematical research and introduces them to a broad range of active interdisciplinary programs related to applied mathematics. (Prerequisite: MATH-606 or equivalent course or students in the ACMTH-MS or MATHML-PHD programs.) Lecture 2 (Spring). |
1 |
| STAT-405 | Mathematical Statistics I This course provides a brief review of basic probability concepts and distribution theory. It covers mathematical properties of distributions needed for statistical inference. (Prerequisites: STAT-205 or MATH-252 or STAT-257 or equivalent courses.) Lecture 3 (Fall). |
3 |
| STAT-406 | Mathematical Statistics II This course is a continuation of STAT-405 covering classical and Bayesian methods in estimation theory, chi-square test, Neyman-Pearson lemma, mathematical justification of standard test procedures, sufficient statistics, and further topics in statistical inference. (Prerequisites: STAT-405 or equivalent course.) Lecture 3 (Spring). |
3 |
| STAT-500 | Senior Capstone in Statistics (WI-PR) This course introduces the student to statistical situations not encountered in regular course of study. It integrates and synthesizes concepts in statistical theory with applications. Topics include open-ended analysis of data, current techniques and practice of statistics, development of statistical communication skills and the use of statistical software tools in data analysis. Each student is required to learn and use a statistical technique beyond what is covered in the previous courses. Students are expected to introduce the method in a presentation and to prepare a comprehensive, professional report detailing the statistical method and its application to a data set. (Corequisites: STAT-305 and STAT-325 or equivalent courses.) Lecture 3 (Spring). |
3 |
| STAT-501 | Experiential Learning Requirement in Statistics The experiential learning (EL) requirement may be fulfilled through a variety of methods including capstone, co-op, undergraduate research, summer research experiences, study abroad relevant to the major, designated EL courses, etc. All experiences must be approved by the School of Mathematical Sciences. Successful completion of the required elements will result in a grade of S in this course. Lecture (Fall, Spring, Summer). |
0 |
Math Graduate Core Courses |
9 | |
General Education - Electives |
9 | |
Open Elective |
3 | |
| Fifth Year | ||
| MATH-790 | Research & Thesis Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor. (This course is restricted to students in the ACMTH-MS or MATHML-PHD programs.) Thesis (Fall, Spring, Summer). |
4 |
Graduate Electives |
15 | |
| Total Semester Credit Hours | 144 |
|
Please see General Education Curriculum for more information.
(WI) Refers to a writing intensive course within the major.
* Please see Wellness Education Requirement for more information. Students completing bachelor's degrees are required to complete two different Wellness courses.
† Students will satisfy this requirement by taking either University Physics I (PHYS-211) and University Physics II (PHYS-212) or General & Analytical Chemistry I and Lab (CHMG-141/145) and General & Analytical Chemistry II and Lab (CHMG-142/146) or General Biology I and Lab (BIOL-101/103) and General Biology II and Lab (BIOL-102/104).
‡ The four program electives must be from the following list of courses: Actuarial Mathematics (MATH-255), Topics in Mathematics of Finance (MATH-261), Stochastic Processes (MATH-505), Introduction to Time Series (STAT-335), Nonparametric Statistics (STAT-345), Multivariate Analysis (STAT-425), Statistical Software - R (STAT-511), Statistical Quality Control (STAT-521), Data Mining (STAT-547), Survey Design and Analysis (STAT-572), Categorical Data Analysis (STAT-584). A program elective is any MATH or STAT course with a course number higher than 250.
Applied Statistics and Data Analytics, BS degree/Applied Statistics, MS degree, typical course sequence
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| First Year | ||
| ISCH-110 | Principles of Computing This course is designed to introduce students to the central ideas of computing. Students will engage in activities that show how computing changes the world and impacts daily lives. Students will develop step-by-step written solutions to basic problems and implement their solutions using a programming language. Assignments will be completed both individually and in small teams. Students will be required to demonstrate oral and written communication skills through such assignments as short papers, homework, group discussions and debates, and development of a term paper. Computer Science majors may take this course only with department approval, and may not apply these credits toward their degree requirements. Lec/Lab 3 (Fall, Spring). |
3 |
| MATH-181 | General Education – Mathematical Perspective A: Project-Based Calculus I This is the first in a two-course sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals. (Prerequisites: MATH-111 or (NMTH-220 and NMTH-260 or NMTH-272 or NMTH-275) or equivalent courses with a minimum grade of B-, or a score of at least 60% on the RIT Mathematics Placement Exam.
Co-requisites: MATH-181R or equivalent course.) Lecture 6 (Fall, Spring). |
4 |
| MATH-182 | General Education – Mathematical Perspective B: Project-Based Calculus II This is the second in a two-course sequence. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates. (Prerequisites: C- or better in MATH-181 or MATH-181A or equivalent course.) Lecture 6 (Fall, Spring). |
4 |
| MATH-199 | Mathematics and Statistics Seminar I This course introduces the programs within the School of Mathematical Sciences, and provides an introduction to math and statistics software. The course provides practice in technical writing. Seminar 1 (Fall). |
1 |
| YOPS-10 | RIT 365: RIT Connections RIT 365 students participate in experiential learning opportunities designed to launch them into their career at RIT, support them in making multiple and varied connections across the university, and immerse them in processes of competency development. Students will plan for and reflect on their first-year experiences, receive feedback, and develop a personal plan for future action in order to develop foundational self-awareness and recognize broad-based professional competencies. (This class is restricted to incoming 1st year or global campus students.) Lecture 1 (Fall, Spring). |
0 |
General Education – Elective |
3 | |
General Education – First-Year Writing (WI) |
3 | |
General Education – Ethical Perspective |
3 | |
General Education – Artistic Perspective |
3 | |
General Education – Natural Science Inquiry Perspective† |
4 | |
General Education – Scientific Principles Perspective† |
4 | |
| Second Year | ||
| MATH-200 | Discrete Mathematics and Introduction to Proofs This course prepares students for professions that use mathematics in daily practice, and for mathematics courses beyond the introductory level where it is essential to communicate effectively in the language of mathematics. It covers various methods of mathematical proof, starting with basic techniques in propositional and predicate calculus and set theory, and then moving to applications in advanced mathematics. (Prerequisite: MATH-173 or MATH-182 or MATH-182A or equivalent course.) Lecture 3, Recitation 4 (Fall). |
3 |
| MATH-251 | Probability and Statistics This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to real-world problems. A statistical package such as Minitab or R is used for data analysis and statistical applications. (Prerequisites: MATH-173 or MATH-182 or MATH 182A or equivalent course.) Lecture 3, Recitation 1 (Fall, Spring, Summer). |
3 |
| MATH-399 | Mathematical Science Job Search Seminar This course helps students prepare to search for co-op or full-time employment. Students will learn strategies for conducting a successful job search and transitioning into the work world. The course meets one hour each week for five weeks. Lecture 1 (Fall, Spring). |
0 |
| STAT-257 | Statistical Inference Learn how data furthers understanding of science and engineering. This course covers basic statistical concepts, sampling theory, hypothesis testing, confidence intervals, point estimation, and simple linear regression. A statistical software package such as MINITAB will be used for data analysis and statistical applications. (Prerequisites: MATH-251.
NOTE: Students cannot receive credit for both MATH-252 and STAT-257 nor for both STAT-205 and STAT-257.) Lecture 3 (Fall, Spring). |
3 |
| Choose one of the following: | 4 |
|
| MATH-221 | General Education – Elective: Multivariable and Vector Calculus This course is principally a study of the calculus of functions of two or more variables, but also includes a study of vectors, vector-valued functions and their derivatives. The course covers limits, partial derivatives, multiple integrals, Stokes' Theorem, Green's Theorem, the Divergence Theorem, and applications in physics. Credit cannot be granted for both this course and MATH-219. (Prerequisite: C- or better MATH-173 or MATH-182 or MATH-182A or equivalent course.) Lecture 4 (Fall, Spring, Summer). |
|
| MATH-221H | General Education – Elective: Honors Multivariable and Vector Calculus |
|
| Choose one of the following: | 3 |
|
| MATH-241 | Linear Algebra This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course. (Prerequisites: MATH-190 or MATH-200 or MATH-219 or MATH-220 or MATH-221 or MATH-221H or equivalent course.) Lecture 3 (Fall, Spring). |
|
| MATH-241H | Honors Linear Algebra |
|
General Education – Global Perspective |
3 | |
General Education – Social Perspective |
3 | |
General Education – Elective |
3 | |
General Education - Immersion 1 |
3 | |
Open Elective |
3 | |
| Third Year | ||
| STAT-641 | Applied Linear Models - Regression A course that studies how a response variable is related to a set of predictor variables. Regression techniques provide a foundation for the analysis of observational data and provide insight into the analysis of data from designed experiments. Topics include happenstance data versus designed experiments, simple linear regression, the matrix approach to simple and multiple linear regression, analysis of residuals, transformations, weighted least squares, polynomial models, influence diagnostics, dummy variables, selection of best linear models, nonlinear estimation, and model building. (This class is restricted to students in the APPSTAT-MS, SMPPI-ACT, or APPSTAT-U programs.) Lecture 3 (Fall, Spring, Summer). |
3 |
| STAT-642 | Applied Linear Models - ANOVA This course introduces students to analysis of models with categorical factors, with emphasis on interpretation. Topics include the role of statistics in scientific studies, fixed and random effects, mixed models, covariates, hierarchical models, and repeated measures. (This class is restricted to students in the APPSTAT-MS, SMPPI-ACT, or APPSTAT-U programs.) Lecture 3 (Spring, Summer). |
3 |
General Education – Immersion 2,3 |
6 | |
General Education – Electives |
6 | |
Program Electives‡ |
12 | |
| Fourth Year | ||
| STAT-405 | Mathematical Statistics I This course provides a brief review of basic probability concepts and distribution theory. It covers mathematical properties of distributions needed for statistical inference. (Prerequisites: STAT-205 or MATH-252 or STAT-257 or equivalent courses.) Lecture 3 (Fall). |
3 |
| STAT-406 | Mathematical Statistics II This course is a continuation of STAT-405 covering classical and Bayesian methods in estimation theory, chi-square test, Neyman-Pearson lemma, mathematical justification of standard test procedures, sufficient statistics, and further topics in statistical inference. (Prerequisites: STAT-405 or equivalent course.) Lecture 3 (Spring). |
3 |
| STAT-500 | Senior Capstone in Statistics (WI-PR) This course introduces the student to statistical situations not encountered in regular course of study. It integrates and synthesizes concepts in statistical theory with applications. Topics include open-ended analysis of data, current techniques and practice of statistics, development of statistical communication skills and the use of statistical software tools in data analysis. Each student is required to learn and use a statistical technique beyond what is covered in the previous courses. Students are expected to introduce the method in a presentation and to prepare a comprehensive, professional report detailing the statistical method and its application to a data set. (Corequisites: STAT-305 and STAT-325 or equivalent courses.) Lecture 3 (Spring). |
3 |
| STAT-501 | Experiential Learning Requirement in Statistics The experiential learning (EL) requirement may be fulfilled through a variety of methods including capstone, co-op, undergraduate research, summer research experiences, study abroad relevant to the major, designated EL courses, etc. All experiences must be approved by the School of Mathematical Sciences. Successful completion of the required elements will result in a grade of S in this course. Lecture (Fall, Spring, Summer). |
0 |
Program Electives‡ |
6 | |
Statistics Graduate Elective |
3 | |
General Education – Electives |
3 | |
Open Electives |
9 | |
| Fifth Year | ||
| STAT-631 | Foundations of Statistics This course introduces principles of probability and statistics with a strong emphasis on conceptual aspects of statistical inference. Topics include fundamentals of probability, probability distribution functions, expectation and variance, discrete and continuous distributions, sampling distributions, confidence intervals and hypothesis tests. (This course is restricted to students in APPSTAT-MS or SMPPI-ACT.) Lecture 3 (Fall, Spring). |
3 |
| STAT-790 | Capstone Thesis/Project This course is a graduate course for students enrolled in the Thesis/Project track of the MS Applied Statistics Program. (Enrollment in this course requires permission from the Director of Graduate Programs for Applied Statistics.) (Enrollment in this course requires permission from the department offering the course.) Thesis (Fall, Spring, Summer). |
3 |
Statistics Graduate Electives |
15 | |
| Total Semester Credit Hours | 144 |
|
Please see General Education Curriculum (GE) for more information.
(WI) Refers to a writing intensive course within the major.
* Please see Wellness Education Requirement for more information. Students completing bachelor's degrees are required to complete two different Wellness courses.
† Students will satisfy this requirement by taking either University Physics I (PHYS-211) and University Physics II (PHYS-212) or General & Analytical Chemistry I and Lab (CHMG-141/145) and General & Analytical Chemistry II and Lab (CHMG-142/146) or General Biology I and Lab (BIOL-101/103) and General Biology II and Lab (BIOL-102/104).
‡ Three of the six program electives must be from the following list of courses: Actuarial Mathematics (MATH-255), Topics in Mathematics of Finance (MATH-261), Stochastic Processes (MATH-505), Introduction to Time Series (STAT-335), Nonparametric Statistics (STAT-345), Multivariate Analysis (STAT-425), Statistical Software - R (STAT-511), Statistical Quality Control (STAT-521), Data Mining (STAT-547), Survey Design and Analysis (STAT-572), Categorical Data Analysis (STAT-584). A program elective is any MATH or STAT course with a course number higher than 250.
Admissions and Financial Aid
This program is STEM designated when studying on campus and full time.
First-Year Admission
A strong performance in a college preparatory program is expected. This includes:
- 4 years of English
- 3 years of social studies and/or history
- 4 years of mathematics is required and must include algebra, geometry, algebra 2/trigonometry, and pre-calculus. Calculus is preferred.
- 2-3 years of science is required and must include chemistry or physics; both are recommended.
Transfer Admission
Transfer course recommendations without associate degree
Courses in liberal arts, physics, math, and chemistry
Appropriate associate degree programs for transfer
AS degree in liberal arts with math/science option
Financial Aid and Scholarships
100% of all incoming first-year and transfer students receive aid.
RIT’s personalized and comprehensive financial aid program includes scholarships, grants, loans, and campus employment programs. When all these are put to work, your actual cost may be much lower than the published estimated cost of attendance.
Learn more about financial aid and scholarships
Research
Undergraduate Research Opportunities
Many students join research teams and engage in research projects starting as early as their first year. Participation in undergraduate research leads to the development of real-world skills, enhanced problem-solving techniques, and broader career opportunities. Our students have opportunities to travel to national conferences for presentations and also become contributing authors on peer-reviewed manuscripts. Explore the variety of mathematics and statistics undergraduate research projects happening across the university.
Latest News
-
September 1, 2022
![a smokestack from a building emitting exhaust.]()
Scientists find the social cost of carbon is more than triple the current federal estimate
After years of robust modeling and analysis, a multi-institutional team including researchers from RIT has released an updated social cost of carbon estimate that reflects new methodologies and key scientific advancements.
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December 8, 2021
![student singing into a microphone.]()
Setting the Stage for the Performing Academic
RIT students have never had as many ways to pursue their love of performing arts than they do now. From scholarships, new clubs and classes, private music lessons, community partnerships, and exciting new venues being built on campus, performing arts for RIT students is literally becoming a show stopper.
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June 23, 2020
![screenshot of program that searches math formulas.]()
RIT researchers create easy-to-use math-aware search interface
Researchers at RIT have developed MathDeck, an online search interface that allows anyone to easily create, edit and lookup sophisticated math formulas on the computer. Created by an interdisciplinary team of more than a dozen faculty and students, MathDeck aims to make math notation interactive and easily shareable, and it's is free and open to the public.
