College of Arts and Sciences

**Student Resources**

- Math Assistance Learning Lab (MALL)
- e-Homework
- Academic Success Center
- Math Test Center
- Common Office Hours for Precalculus and Calculus
- Math Course Materials
- Helmke Library
- IPFW Bulletins

Major topics include divisibility theory, Euclidean Algorithm, prime numbers, congruences, Fermat's little theorem, number theoretic functions, and quadratic reciprocity. Other topics include cryptography and perfect numbers, as time permits.

Text: *Elementary Number Theory*, 7th edition, by David M. Burton.

Prerequisite: Any mathematics course where proofs were given in class or expected of the students. See the instructor if you have a question about your background.

Instructor: Robert Vandell, Ph. D.

Robert Vandell received a Ph. D. from Western Michigan University in 1996.

Time and location: MTWR 5:30-7:15 p.m., June 29 to August 7.

This course will cover calculus of functions of several variables and vector fields in orthogonal coordinate systems; optimization problems; Green's, Stokes', and Divergence Theorems; and some applications to engineering and physical sciences.

Text: *Introduction to Vector Analysi*s, 7th edition, by Davis and Snider

Prerequisite: MA 261 or 263. If you have a question, call the instructor at 481-6976.

Instructor: Safwan Akkari, Ph.D.

Safwan Akkari joined the IPFW faculty in 1988. He has a B.S. from the Lebanese University and an M.S. from the University of Tennessee Space Institute. He received a Ph.D. from Louisiana State University in 1988. His research interests are in matroid theory and graph theory.

Time and location: TR 6-7:15 p.m. in Kettler G47.

MA 521 is an introduction to optimization and its applications. The course starts with a review of some concepts from linear algebra and multivariate calculus, followed by unconstrained optimization methods, with applications to neural networks and least squares optimization. Constrained optimization is illustrated with linear programming and its nonlinear analogue, convex programming.

Text: *An Introduction to Optimization*, 4th edition, by Edwin K. P. Chong and Stanislaw H. Zak.

Prerequisite: A course in vector calculus or advanced calculus, and a linear algebra course. See the instructor if you have a question about your background.

Instructor: Peter Dragnev, Ph.D.

Peter Dragnev studied at the University of Sofia and the Institute of Mathematics of the Bulgarian Academy of Sciences. He received a Ph.D. from the University of South Florida in 1997. His research interests are in analysis, in particular, approximation theory and potential theory.

Time and location: MW 4:30-5:45 p.m. in Kettler 216

Stat 514 is an introduction to statistical designs that involve planning, conducting experiments, and analyzing the resulting data. The major objective of such designs is to develop a process that is affected minimally by external sources of variability. In this course, the focus is on experiments in engineering and in the chemical sciences. Latin squares, factorial designs, and fractional factorial designs will be discussed. Some background in regression analysis is recommended. Instructor and students will use the statistical software MINITAB.

Text: *Design of Experiments*, 8th edition, by Montgomery.

Prerequisite: STAT 512 or instructor's permission.

Instructor: Chand K. Chauhan, Ph.D.

Chand Chauhan received a Ph.D. from the Ohio State University and has taught at IPFW since 1983. She has conducted seminars and taught short courses in statistics for several area companies. Chauhan has also done consulting work for individuals as well as for companies. She has published and presented papers on the design of experiments.

Time and location: TR 6-7:15 in Kettler 216.

This course is an introduction to mathematical statistics. Topics include distributions of functions of random variables, especially the distributions of statistics when sampling from a normal distribution; the Central Limit Theorem and other limit theorems; point estimation and confidence intervals; properties of estimators; theory of statistical hypothesis tests, including tests based on normal models; and other topics as time permits.

Text: *Introduction to Probability & Statistical Inference* by Roussas.

Prerequisite: STAT 519 (Mathematical Probability)

Instructor: Yvonne Zubovic, Ph. D.

Yvonne Zubovic received a Ph. D. from The Ohio State University in 1988 and has taught at IPFW since 1991. In 1997, she received the Outstanding Teacher award for IPFW. Her main research interests are in biostatistics.

Time and location: MW 6-7:15 in Kettler 218.

This course is an introduction to graphs and networks, with applications. Topics include trees, connectivity, matchings, planarity, chromatic numbers, directed graphs, tournaments, and a variety of applications.

Text: *Graphs and Digraphs*, 5th ed., by G. Chartrand, L. Lesniak, and P. Zhang.

Prerequisite: MA 305 or 351. (A sophomore-level linear algebra course will provide the necessary level of mathematical maturity.) Please ask the instructor if you have a question about your background.

Instructor: Lowell W. Beineke, Ph.D.

Lowell W. Beineke received his Ph.D. from the University of Michigan and is the Schrey Professor of Mathematics. He has won several teaching awards and has published more than 100 papers and several books in graph theory.

Time and location: TR 4:30-5:45 in Kettler 118.

In MA 540 (and 541) we examine some fundamental topics from calculus with closer attention to theory and proof. In the setting of metric spaces we study sequences and continuous functions, using the concepts of completeness, compactness, and connectedness.

Text: *Introduction to Analysis* by Maxwell Rosenlicht.

Prerequisite: A grade of C or better in MA 441 (Real Analysis) or its equivalent.

See the instructor if you have a question about your background.

Instructor: Cecilia Weakley, Ph. D. (weakley (at) ipfw.edu ; (260)-481-6233)

Cecilia Weakley received a Ph.D. from the University of North Carolina at Chapel Hill and has taught at IPFW since 1989. She has published papers in measure theory and functional analysis.

Time and location: Tuesdays and Thursdays, 4:30-5:45 p.m., starting August 26, in Kettler G29.

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Description: An introduction to the mathematical theories of error-correcting codes and cryptography. Linear codes; cyclic codes; the Hamming, Golay, BCH, and Reed-Muller codes; maximum likelihood decoding. History of cryptographic techniques; symmetric-key cryptography (DES, AES); public-key cryptosystems and related techniques; protocols for information security.

Text: *Coding theory and Cryptography: The Essentials*, 2nd edition, Hankerson et al, CRC Press. Material from chapters 1-5 and 10-12 will be covered.

Outline:

●Introduction to error-correcting codes. (1.5 weeks)

●Linear codes. (1.5 weeks)

●Perfect codes, the Hamming and Golay codes. (2 weeks)

●Cyclic linear codes. (1.5 weeks)

●BCH codes over finite fields. (1.5 weeks)

●Introduction to cryptography; historical cryptosystems and cryptanalysis. (1.5 weeks)

●Symmetric key systems, DES and AES. (2 weeks)

●Public-key cryptosystems (RSA, ElGamal) with number-theoretic underpinnings. (3 weeks)

●Cryptographic protocols. (1 week)

Prerequisite: MA 351 or an equivalent linear algebra course with a grade of C or better.

Instructor: Professor Robert Vandell (vandellr (at) ipfw.edu; 260-481-6186)

Robert Vandell received a Ph. D. from Western Michigan University in 1996. His research in graph theory has interested him in coding theory.

Time and location: Mondays and Wednesdays, 4:30-5:45 p.m., starting August 25, in Kettler 218.

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Topics covered include inference in simple and multiple linear regression, polynomial regression, model building with real data; one-way and two-way analysis of variance, analysis of covariance; use of existing statistical computer programs.

Text: *Applied Linear Statistical Models*, special 5th edition, by Kutner, Nachtsheim, Neter, and Li. (This text consists of several chapters from the standard 5th edition.)

Prerequisite: A statistics course similar to STAT 511, 517, or 528. See the instructor if you have a question about your background.

Instructor: Yihao Deng, Ph. D. (dengy (at) ipfw.edu ; (260)-481-4185)

Yihao Deng joined the faculty in fall 2006, after receiving his Ph.D. in statistics from Old Dominion University. His areas of specialization include longitudinal data analysis, regression analysis, and generalized linear models. He has done consulting work on leadership and organizational change, youth violence prevention, adolescent ADHD, and other topics.

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This course is an introduction to probability as a foundation for statistics. Topics include sample spaces and random variables; joint, conditional, and marginal distributions, special discrete and continuous distributions; moment generating functions, distribution of functions of random variables; limit theorems.

Text: *An Introduction to Probability and Statistical Inference* by George Roussas.

Prerequisite: Multivariable calculus. See the instructor if you have a question about your background.

Instructor: Yvonne Zubovic, Ph. D.

Yvonne Zubovic received a Ph. D. from The Ohio State University in 1988 and has taught at IPFW since 1991. In 1997, she received the Outstanding Teacher award for IPFW. Her main research interests are in biostatistics.

Time and location: 6-7:15 p.m. Mondays and Wednesdays in Kettler 218, starting August 25.

The course will describe the origins of mathematical concepts and

their evolution over time, from early number systems to recent results

in the foundations of mathematics. In addition to the mathematical

ideas themselves, we will consider the role of applications in their

development, and connections between society and mathematics through

the ages.

Text: *The History of Mathematics: An Introduction*, by David M. Burton, 7th edition.

Prerequisite: At least a year of calculus. Some background in

mathematical proof-writing.

Instructor: Betsy Berry, Ph. D.

Betsy Berry received her Ph. D. in mathematics education from Purdue University in 2007. As an undergraduate and master's student, she had the opportunity to study with the inimitable math historian, Dr. Howard Eves at the University of Maine and is looking forward to bringing his enthusiasm and expertise and passion for the history of math into her teaching of this course.

Time and location: MTWR 5:30-7:15 p.m. in Kettler 216, June 30 - August 8.