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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.


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 - Data Visualization OR course - Data Visualization

  • course - Applied Data Analysis

  • course - Modeling and Simulation