Mathematics has long been regarded as a natural component of a liberal arts education because of its strongly analytical, problem-solving emphasis. More recently, our technological and data-driven society has brought increased recognition of the importance of mathematical and statistical reasoning, making a mathematics, statistics or actuarial science major (or a math, math teaching or stats minor) an excellent choice for anyone considering a career in industry, scientific research, data analysis, predictive modeling, engineering or education.
At Northwestern, we believe that the utility of mathematics for those and other fields follows from its power as a universal language. Mathematics and statistics courses offered here are designed to develop and sharpen your skills in this language in part because increased mathematical understanding can bring an increased awareness of and appreciation for the order behind God’s creation and for the attributes of God reflected in creation.
We also believe that mathematics is one and eternal, shining forth from the mind of God. That we can comprehend some part of mathematics is evidence that human beings are created in the image of God. That the one and eternal God has enabled our mathematical discovery is an excellent reason to deepen our understanding of mathematics.
MAT 112QR -
(4 credits) (NWCore option under Quantitative Reasoning) This course is a
study of functions, limits, derivatives and integrals with a strong
emphasis on both theory and applications.
Note: Meets four times per week.
Prerequisites: C- or higher in MAT109, or an ACT math score of at least
24 (SAT 570 or above), or permission of mathematics department chair.
MAT 180WI -
Logic and Discrete Mathematics
(3 credits)(Writing intensive) An introduction to the language and logic of
mathematical proof via topics in discrete mathematics. Topics will include
logic, elementary number theory, basic set theory and methods of
mathematical proof (direct proof, indirect proof, induction).
Note: Other topics will be chosen from counting, functions, relations,
recursion and graph theory.
Prerequisite: C- or better in MAT 112QR or permission of instructor.
MAT 211 -
A study of transcendental functions, techniques of integration, improper integration, sequences, series, polar coordinates and conic sections.Prerequisite: C- or better in MAT112 or permission of instructor.(4 credits)
MAT 212 -
A study of the cylindrical and spherical coordinate systems, vectors in two dimensions and three dimensions, vector valued functions, functions of several variables, multiple integration, and vector calculus.Prerequisite: C- or better in MAT211 or permission of instructor.(4 credits)
MAT 316 -
Probability and Statistics I
A post-calculus course in probability and statistics, which develops the theory of discrete and continuous distributions, expected value, random variables and inferential statistics.Prerequisites: C- or better in MAT116 or 117, 180, 211 or permission of instructor.(3 credits, alternate years, consult department)
MAT 317 -
A study of the algebra of matrices and vector spaces including matrix operations, systems of equations, determinants, properties of real vector spaces, eigenvalues and eigenvectors.Prerequisite: C- or better in
MAT112QR and 180 or permission of instructor.(3 credits)
MAT 375 -
Econometrics with Regression Analysis
This course, which is required for finance, economics, and actuarial science
majors, is designed to introduce students to the fundamentals of econometric
analysis. To this end, the primary focus is on simple and multiple linear
regressions using cross-sectional data and time series regressions. We will
also discuss highly useful extensions including regression with binary
dependent variables, and regression analysis using panel data if time. The
course will put a heavy emphasis on empirical applications; econometric
theory will be discussed where necessary but will not be the central focus.
Instead, we focus on estimating regression models using statistical packages
such as R, SPSS, or Stata, and on interpreting the results. Both estimation
and interpretation are highly marketable skills. The coverage of this course
will be sufficient for SVEE Applied Statistics (SOA) and useful for CFA
exams. More broadly, what you learn from this course will be valuable for a
career in consulting, banking, insurance, and other related fields.
Prerequisite: C- or better in MAT112QR and in MAT116QR or 117QR. (4 credits) Cross-referenced in economics.
MAT 416 -
Probability and Statistics II
A continuation of Probability and Statistics I. Emphasis will be placed on functions of random variables and sampling distributions.Prerequisite: MAT316.(3 credits, alternate years, consult department)
MAT 445 -
A course focusing on the theory and objectives critical to the design and
implementation of sound statistical experiments and surveys, including
survey and experimental methods. Emphasis on sampling techniques, instrument
design, reliability and validity. Prerequisite: MAT 375. (3 credits; alternate years, consult
MAT 450SR -
This course will provide you with a survey of some of the fascinating and
critical ideas in mathematics, including historical proofs of some results
which are familiar to you through your previous mathematical study as well
as some results which will be new to you. We will also spend a significant
amount of time discussing connections between mathematics and the Christian
faith, and we'll take a look into the background of the mathematically and
scientifically significant number 0, which has had its own theological
issues. And you'll explore the contributions of the various parts of your
college experience to the goals of the IGE program and your progress in
establishing personal commitments and a sense of vocation. Prerequisites: grade of C- or better in MAT211 or permission of
instructor. (2 credits)
Choose one course:
MAT 330 -
A course building student skills in working with large data sets gathered
from real-world studies and experiments. Students will learn and experience
best practices for data-type, range, constraint, code, cross-reference,
structured, and textual validation. Prerequisites: CSC 170 and MAT 375. (3 credits; alternate years, consult
MAT 385 -
Advanced Regression Analysis
A course building on simple and multiple linear regression analysis to
introduce multivariate analysis, logistic regression, moderation, matric
formulation, residual analysis, transformations, regression diagnostics,
multicollinearity, and variable selection techniques. Prerequisite: MAT375. (3 credits; alternate years, consult
MAT 435 -
An introduction to Bayesian statistical modeling and inference and related
computational strategies and algorithms, including posterior and predictive
inference; Bayesian models in applications; methods of prior elicitation;
and computation, visualization, and analysis of real-world data. Prerequisites: MAT 116QR and MAT 180WI. (3 credits;
alternate years, consult department)
CSC 170 -
In today's data-driven world, statistical literacy and data analysis are
increasingly important skills. This course introduces students to the
fundamental aspects of programming, such as data types, procedural
abstraction, control structures, and iteration, with a focus on the
application of these concepts to statistics and data analysis. Topics will
include the programmatic implementation of summary statistics, correlation,
linear modeling, and clustering. A statistics-focused language, such as R,
is covered in-depth for the purpose of gaining mastery of these principles. Prerequisites: C- or better in MAT 090 or Math ACT subscore of 20 or above (SAT 510 or above).
CSC 291 -
Database Management Systems
This course examines database concepts, theory, design and management. Emphasis will be on the relational model. Topics will also include normalization, query languages, database recovery and security aspects. This course will include experience with a relational database system and programming database access into computer applications via a high-level programming language.Prerequisite: CSC171.(4 credits; alternate years, consult department)
CSC 310 -
Data visualization provides insight into unfamiliar data sets, identifies
issues in statistical models, and helps effectively communicate results.
This course will focus on all of these aspects, starting with exploratory
and evaluative techniques and progressing to creating professional,
publication-quality visualizations. The classroom experience will alternate
between discussion of best practices and case studies and hands-on learning
of industry-standard visualization programming librarie, and culminate with
a comprehensive visualization project. Prerequisites: CSC 170 or CSC 171QR. (4 credits; alternate years, consult
Total credits required: 49