At least the following courses counting towards the Minor will be offered. There may be others:
- courses we missed when checking the Bulletin, and
- courses courses that can count despite not being listed in the Bulletin—especially new offerings and special topics courses.
(Official requirements are in the Bulletin text and substitutions are subject to University approval.)
Category A. Philosophy of Science
PHI 152 (QR) Scientific Reasoning
There may or may not be a Scientific Method. But there are definitely scientific methods. What are they? How and why do they work? And when science fails, what are some ways it fails? We will learn, use, and debate ideas about how to think scientifically. And we will observe science succeeding and failing in case-studies from current research and the history of science.
Category B. Statistical Reasoning
MATH 008 Elementary Mathematical Statistics
This course examines frequency distributions, averages, graphical representations of data, measures of dispersion, types of distribution, estimation, hypothesis testing, curve fitting, and correlation.
MATH 045 (MA) Logic, Sets, and Probability
Logic, sets, probability.
MATH 138 (MA) Mathematical Probability and Statistics
The following topics are covered over two semesters in MATH 137 and this course: discrete and continuous probability distributions, characteristics of distributions, sampling theory, estimation, hypothesis testing, correlation, regression and other topics.
PSY 040 Statistics
Topics include the role of statistics in the scientific method, descriptive statistics, z scores and the standard normal distribution, sampling distributions and statistical inference, hypothesis testing, the t distribution, simple and factorial analysis of variance, correlation and regression, and nonparametric statistics.
SOC 180 Statistics in Sociology
Use of basic statistical analyses to examine sociological data. Topics include measures of central tendency and dispersion, probability, inference and hypothesis testing, correlation and regression, analysis of variance, and nonparametric techniques. A component on the utilization of computers for statistical analysis is included.
Category C. Computing for Data Analysis
CSC 015 (CS) Fundamentals of Computer Science I: Problem Solving and Program Design
Introduction to computer science with emphasis on problem solving, programming and algorithm design. Uses a high-level programming language for solving problems and emphasizing program design and development. Topics include basic programming constructs, expressions, functions, data types, arrays and strings.
Category D. Electives
CSC 016 (CS) Fundamentals of Computer Science II: Data Structures, Algorithms and Object-Oriented Programming
Continuation of CSC 15. Introduction to classes and objects. Investigates the essential properties of data structures, abstract data types, algorithms for operating them, use of these structures as tools to assist algorithm design. Introduces searching and sorting techniques.
ECO 184 (BH) Empirical Methods in Economics
An introduction to statistical methods and tools used in applied economic research. Topics include fundamental statistical concepts including probability, random variables, probability distribution and density functions, sampling distributions, estimation, and hypothesis testing. Students will be introduced to the preparation and use of empirical data and popular software packages for the purpose of estimation and inference with the linear regression model.
IT 117 Database Management Systems
Advanced course on database management systems (DBMS) concentrating on the relational data model and the SQL language. Covers theory of the relational data model contrasting it with earlier models. Database design is developed in the context of the overall design of an information system in accounting, finance, management, marketing, and other application areas. Topics include conceptual, logical, and physical database design, including data normalization and integrity constraints. Distributed database systems in a global business environment and issues related to data accuracy, security, privacy, and threat to individual rights are explored. Course requires designing and implementing databases using a mainframe and/or micro DBMS.
PSY 141 Research Methods and Design
Major principles of research and data collection techniques in experimental psychology. Laboratory work with animals and/ or human beings includes research in selected topics. An oral presentation is required.