STATn - Statistics Minor
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Program Description
Effective: Fall 2017
Modifications Made to Curriculum: Fall 2021
Statistics is the practice of working with data using computational and quantitative techniques: collecting, organizing, modeling, analyzing, summarizing, and visualizing, often in order to make well-founded inferences or predictions from data. Statistical methods and ways of thinking are important in many disciplines, from physical sciences to the humanities; and statistical evidence is crucial for high-stakes decision-making in realms like medicine, public policy, and finance.
The ability to handle and think critically about data, and to understand the design, assumptions, and limitations of statistical analysis and studies fit well within a liberal arts education. Drew’s statistics program has a strong computational, applied, and interdisciplinary focus that prepares students to participate in quantitative research and careers, to apply statistics in their areas of study, and to better understand, improve, and protect the world in which we live.
Requisites
Requirements for the Minor (24 credits)
I. Core (12 credits)
Complete all of the following:
course - Introduction to Statistics
course - Intermediate Statistics OR course - Economic Methodology And Introductory Econometrics
A course with a course prerequisite that uses statistics in the context of another discipline (such as course, course, course , or course) OR an additional elective from the list below
II. Elective Courses (12 credits)
Complete 12 credits, selected from among the following:
course - Cryptocurrency Investing
course - Statistical Computing in R
course - Special Topics in Statistics
course - Sports Statistics
course - Text Mining
course - Applied Regression Analysis
course - Statistical Theory
course - Bayesian Statistics
course - Statistical Machine Learning
course - Applied Data Analysis
course - Modeling and Simulation