B.S. in Applied Statistics
Long Beach , United States
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Details
Program Details
Degree
Bachelors
Major
Applied Statistics | Mathematics | Statistics
Area of study
Mathematics and Statistics | Natural Science
Course Language
English
About Program
Program Overview
Program Overview
The B.S. in Applied Statistics is a comprehensive program that aims to equip students with a deep understanding of mathematical concepts and techniques. The program covers a wide range of fields, including single and multivariate calculus, linear algebra, real analysis, probability/statistics, basic differential equations, and mathematical modeling.
Program Objectives
The program is designed to help students demonstrate:
- Mastery of basic mathematical ideas and techniques
- Understanding of the nature of proof
- Ability to think analytically and critically, and to formulate problems, solve them, and interpret their solutions, both collaboratively and individually
- Ability to use technological tools, such as algebraic and visualization software, statistical packages, and a high-level programming language
- Proficiency in communicating complex results to a diverse audience with clarity
- Commitment to collecting and managing data responsibly and ethically, and the ability to discern appropriate methods for analyzing various types of data
- Proficiency in coding and computation for organizing, summarizing, and analyzing raw data collected from a diverse array of contexts, using technology to draw conclusions and make actionable decisions
- Ability to think critically and abstractly about the mathematical foundations for statistics and data science, and their application to real data
- Skill in collaborative problem solving for large-scale projects involving data from a wide variety of domains
Program Details
The program focuses on developing students' skills in:
- Mathematical modeling
- Data analysis and interpretation
- Statistical reasoning and thinking
- Communication of complex results
- Responsible and ethical data collection and management
- Coding and computation for data analysis
- Collaborative problem solving
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