Program Overview
The Statistics minor provides students with a comprehensive understanding of statistical concepts and research skills. It strengthens their grasp of statistical inference, methods, and computing packages. The program offers tailored coursework for math and non-math majors, equipping them for careers and graduate studies in natural and social sciences.
Program Outline
Degree Overview:
Overview: The Statistics minor is designed for students seeking a comprehensive understanding of statistics to enhance their competitiveness in employment and graduate studies in natural and social sciences. This program strengthens students' grasp of statistical concepts and sharpens their research skills. Objectives: The program aims to provide students with a solid foundation in statistics through education and training. The specific objectives include:
- Developing a clear understanding of the theoretical basis of statistical inference and reasoning.
- Acquiring knowledge of statistical methods commonly used in practice, such as regression, analysis of variance, experimental design, and design of statistical surveys.
- Gaining competency in using statistical computing packages like SAS, R, and SPSS.
- Enhancing the ability to apply statistical knowledge in practice, including designing surveys and experiments, collecting, processing, and analyzing data, and summarizing, interpreting, and presenting results effectively.
Outline:
Core Requirements (8 credits):
- STAT 2090 - Statistical Computing (2 credits)
- STAT 3050 - Statistical Modeling (3 credits)
- STAT 4287 - Applications of Statistics (3 credits) Minor Courses for Math Major (15 credits):
- MATH 1530 - Probability and Statistics - Noncalculus (3 credits)
- STAT 4047 - Mathematical Statistics I (3 credits)
- STAT 4057 - Mathematical Statistics II (3 credits)
- STAT 4217 - Statistical Machine Learning (3 credits)
- STAT 4307 - Sampling and Survey Techniques (3 credits) Minor Courses for Non-Math Major (19 credits):
- MATH 1530 - Probability and Statistics - Noncalculus (3 credits)
- MATH 1910 - Calculus I (4 credits)
- MATH 2010 - Linear Algebra (3 credits)
- MATH 2050 - Foundations of Probability and Statistics - Calculus Based (3 credits)
- STAT 4217 - Statistical Machine Learning (3 credits)
- STAT 4307 - Sampling and Survey Techniques (3 credits)