274 Statistics Degree Programs in USA

American University’s Master of Science in Statistics is an excellent way to further your mathematical education, prepare for a doctoral program, or gain the expertise to advance your career. In this program, you will develop proficiency in the development, research, and analysis of quantitative tools to turn ideas into intelligent, informed actions. Incoming students can qualify for merit awards as Graduate Assistants or Research Assistantships to gain experience. We offer two different tracks to help you match your course of study to your intellectual and professional goals. The mathematical statistics track is for those intending to pursue a Ph.D. in statistics, while the applied statistics track is perfect for those intending to use their statistical expertise in the workplace. Whichever track you follow, AU’s MS in Statistics is your key to success.

Be competitive in today’s world of data science by combining theoretical knowledge with practical skills. Learn and master techniques for collecting, organizing, and analyzing data, and gain valuable experience defining and solving problems in practical settings.

The Master of Science in Statistics program is ideal for students who are preparing for professional positions or doctoral programs in statistics and other quantitative fields. Thesis and non-thesis options are available, and students may enroll full-time or part-time. Use of statistical software packages, available in all university computer labs, is required for most courses.

Statistics is the science of analyzing numerical data and has applications in a variety of fields. At JMU, you will get the best of both worlds: in-depth faculty-student collaborative experiences usually only found in smaller liberal arts institutions, along with the breadth and diversity of offerings of a large institution. Our faculty is committed to incorporating student projects into their research and guiding undergraduates through the processes of proposing and carrying out professional-level research projects in statistics. In addition, our conferences, clubs, and outreach programs designed specifically for undergraduates make our majors true members of our community.

The Master of Arts in Statistics degree program provides advanced training in the fundamental theory of statistics and probability and in their applications to a broad range of disciplines. This program prepares students for positions in education, government agencies, industry, or nonprofit institutions, or for further graduate study leading to a PhD degree.

Created in 1989, the Applied Statistics Program at Syracuse University is an interdisciplinary program within the College of Arts and Sciences that includes faculty from computer and information science, management, mathematics, psychology, and the social sciences, among others. The program offers an undergraduate concentration in applied statistics, sponsors a speakers series that hosts visiting statisticians and scientists, and offers a master’s degree in applied statistics.

The Applied Statistics MSc program is designed to give students a strong foundation in statistical theory and practical skills. It covers a broad range of topics, including data analysis, probabili...

The B.S. degree in Math with a Statistics concentration is a robust program that is suitable for students who would like to pursue graduate study or for those who desire a strong foundation for math-related careers or research that require analytical and critical thinking, problem-solving, and statistical analysis skills. Students are encouraged to pursue research and internship opportunities. The concentration technical electives pave the way for students to complete coursework in a minor or related areas, such as Data Science, Artificial Intelligence, Computer Engineering, and Economics, to name a few. Nevertheless, students have the flexibility to select electives in other fields of personal interest.

The advanced certificate in applied statistics is designed for engineers, scientists, analysts, and other professionals who want a solid education in the statistical methods that are most closely related to their work.

The Bachelor of Science in Statistics is designed to provide a framework for students to develop connections between statistical concepts and theories, their impact on data science, and applications to statistical practice. It will prepare statisticians to use modern statistical techniques to design studies, collect data, analyze and visualize high dimensional data sets, and draw valid conclusions in an increasingly data-centric world. In this program, students will meld the time-tested concepts and theories of statistics with modern methods of analysis, in order to interpret the data that is collected in nearly every discipline and every sector of industry and government.

The B.A. degree in Math with a Statistics concentration is a flexible program that provides a foundation in mathematics and training for graduates to succeed in careers that demand statistical skills. Students in this concentration are encouraged to complement coursework with a minor or second major to reflect the student’s personal career interests.

Random variables, independence, and conditional probability; discrete and continuous distributions, moments, and distributions of several random variables. Topics in mathematical statistics: random sampling, point estimation, confidence intervals, hypothesis testing, non-parametric tests, regression and correlation analyses; applications in engineering, industrial manufacturing, medicine, biology, and other fields. Prerequisite: CME 100/ENGR154 or MATH 51 or 52.

Introduces basic statistical modeling techniques. One- or two- sample inference for unknown means, proportions and variances, categorical data analysis, introduction to design of experiments and analysis of variance, analysis of simple and multiple linear regression models, non-parametric methods.

Basic concepts of estimation and tests of hypotheses, ideas from probability; one-, two-, and multiple-sample problems. Applications are in the social sciences, and students will be able to understand the basics of using a sample to predict uncertainty.

Numerical and graphical summaries of univariate and bivariate data. Basic probability, random variables, binomial distribution, normal distribution. One-sample statistical inference for normal means and binomial probabilities. Primarily for students in the social sciences with limited mathematics preparation.

Introduction to the logic and processes involved in descriptive and inferential statistics for psychology. Topics include statistical inference, significance, t-tests, ANOVAs, correlation, regression, and statistical software analysis. This is a hybrid class: class time is reserved for hands-on activities.