Program Overview

Program Overview

The provided content does not directly describe a university program but rather outlines various aspects of a university's offerings, including programs, admissions, and study abroad opportunities. However, it does detail a specific course, "Practicum in Applied Statistics: Applied Probability," which can be considered a part of a broader program in Applied Statistics.

Course Details

Course Description

This course covers foundational topics in probability and statistics, including Kolgomorov's axioms of probabilities, set theory, discrete combinatorial probability, Bayes' theorem, probability distributions, and the assumptions of dependence and independence. It also introduces sampling distributions, the law of large numbers, and the central limit theorem. The course combines theoretical approaches with simulation-based illustrations using the statistical programming language R.

Course Information

• Course #: APSTA-GE 2351
• Credits: 3
• Department: Applied Statistics, Social Science, and Humanities

Faculty

• Professor: Daphna Harel, Associate Professor of Applied Statistics and Director of the A3SR MS Program, Steinhardt School of Culture, Education, and Human Development

Program Structure

While the specific structure of the program that includes the "Practicum in Applied Statistics: Applied Probability" course is not detailed, the course itself suggests a program that emphasizes both theoretical foundations and practical applications in statistics, potentially catering to students interested in applied statistics, social sciences, and humanities.

Admission and Tuition

Information on admission criteria, tuition fees, and specific program requirements is not provided in the given context. For detailed information on these aspects, prospective students would need to consult the university's official resources or contact the admissions department directly.

Research Areas

The course's focus on applied statistics, probability, and the use of statistical programming languages like R indicates that the program may involve research in areas such as data analysis, statistical modeling, and applied research in social sciences and humanities. However, specific research areas or opportunities within the program are not outlined in the provided content.

Conclusion

The "Practicum in Applied Statistics: Applied Probability" course is part of a broader academic offering that likely includes a range of programs in applied statistics and related fields. For comprehensive details about program specifics, including admissions, tuition, and research opportunities, interested individuals should refer to the official university website or contact the relevant department directly.