Fall 2020

Statistical methods for business analysis; exploration and visualization of large data sets; simulation; hypothesis testing, multiple regression modeling, and confidence intervals. Extensive computer applications. (Duplicates credit in BUAD 310 and former ITP 251)

Investigation and design of elements and systems for buildingstructures; applied mechanics, strength of materials, structuralinvestigation as a design tool. Recommended preparation: PHYS 125 and MATH 108

Statistical methods in biological science and medicine, including populations and samples, random sampling, confidence intervals, paired samples and regression.

Statistical methods for business analysis; data exploration and description; sampling distributions; estimation; hypothesis testing, simple and multiple regression; model building. Extensive computer applications. (Duplicates credit in BUAD 312 and the former ITP 251.)

Statistical methods for business analysis; exploration and visualization of large data sets; simulation; hypothesis testing, multiple regression modeling, and confidence intervals. Extensive computer applications. (Duplicates credit in BUAD 310 and former ITP 251)

Experimental and survey methods for communication study; basic statistical concepts, procedures, and tests.

A behind-the-scenes overview of the computational/algorithmic principles that form the basis of today's digital society. Exploration areas include social media, web search, videogames and location-based services.

Behavior of firms and consumers, functions of the price system, competition and monopoly, labor markets, poverty, government regulation, international trade, and the environment.

Unemployment, inflation and output determination and links.Effects of government taxation and spending on growth, investment,saving, consumption, and trade.

Analysis and manipulation of data and information related to quantifiable objects, symbolic elements, or logic; formal reasoning, abstract representation, and empirical analysis. (Satisfies GE-F, Quantitative Reasoning). Open only to Freshmen.

Intermediate statistics for health behavior studies; topics include descriptive statistics, hypothesis testing, correlation and regression, and use of computer software in data analysis.

Examines the primary goals and methods of epidemiology, the study of factors that influence health and disease in individuals and populations.

Introduction to theoretically oriented research approaches and designs; emphasis on the logic of argumentation.

Empirical study of the sounds and structures of human language;syntax and semantics; language change; linguistic universals.

Study of language as a complex natural system that requires elaborate mental computation.

Equations and inequalities; functions; graphs; polynomial and rational functions; exponential, logarithmic, and trigonometric function; analytic geometry.

An introduction to the basic tools of statistics. Descriptive statistics; probability; expected value; normal approximation sampling; chance models; tests of significance. Recommended preparation: MATH 040x or math placement exam. Not available for major credit to Math students.

Functions, graphs, polynomial and rational functions, exponential and logarithmic functions, matrices, systems of linear equations.

Derivatives; extrema. Definite integral; fundamental theorem of calculus. Extrema and definite integrals for functions of several variables. Not available for credit toward a degree in mathematics. Prerequisites: MATH 108 or MATH 117 or placement exam in MATH.

Limits; continuity, derivatives and applications; antiderivatives; the fundamental theorem of calculus; exponential and logarithmic functions.

A continuation of MATH 125: trigonometric functions; applications of integration; techniques of integration; indeterminate forms; infinite series; Taylor series; polar coordinates.

Vectors, vector valued functions; differential and integral calculus of functions of several variables; Green's theorem, Divergence theorem, Stoke's theorem.

Fundamental basis for various statistical tests, underlying assumptions, and statistical analyses used in biomedical and clinical research.

Critical analysis and reasoning skills required to solve scientific problems in human behavior, including presentation of data, logic of research design, statistics, and research ethics. Not for major credit for Psychology majors.

Introduction to the use of statistics in psychology: basic ideas in measurement; frequency distributions; descriptive statistics; concepts and procedures in statistical inference.

Sociological measurement, univariate description, elementary correlation, introduction to statistical inference.

The role of formal reasoning, abstract representation and empirical analysis in building maps for sharing knowledge across the physical, life and social sciences and humanities.