Mark Werness portrait

Mark Werness

Associate Professor and Chair
Degree
Ph.D., M.S., University of Minnesota
B.A., Carleton College
Office
OSS 403
Phone
(651)962-5471
Toll Free
(800) 328-6819 ext. 5471
Mail
University of St. Thomas
Mail Number OSS 402
2115 Summit Avenue
St. Paul, MN 55105

Professional Interests

My current academic interests are applied statistics, computer applications in experimental science, and STEM teacher preparation.  In addition, I was the first Program Director for the new Statistics major at UST, fall 2009 to summer 2011.  

Spring 2016 Courses

Spring 2016 Courses
Course - Section Title Days Time Location
CISC 230 - 02 Object Oriented Design & Prog See Details * *
CRN: 21643 4 Credit Hours Instructor: Mark E. Werness (Formerly QMCS 281) Programming and problem solving using an object-oriented approach. Builds on the procedural language foundation developed in CISC 130 or 131. Topics include: how procedural design differs from object-oriented design, algorithms, modeling, design requirements and representation, Uniform Modeling Language specification, implementation of object-oriented models, testing, and verification, and elementary design patterns. Lab included Prerequisites: A minimum grade of C- in CISC 130 or 131

Schedule Details

Location Time Day(s)
OSS 4321525-1700M - W - - - -
OSS 4321330-1510- - - R - - -
STAT 220 - 04 Statistics I M - W - F - - 0935 - 1040 OSS 329
CRN: 20841 4 Credit Hours Instructor: Mark E. Werness Formerly IDTH 220 or QMCS 220 Introductory applied statistics. Work environment; population, sampling frame, random sample, type of variables and studies. Descriptive statistics: collecting, displaying, summarizing, and interpreting data to extract information. Probability; relative frequency definition of probability, conditional probability, independence, discrete and continuous random variables, probability distribution and probability density, binomial, normal, standard normal, t, chi-square, and F distributions. Inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at level of MATH 111 or above; or MATH 100, 101, 105, 108, 109, 111 or 113 NOTE: Students who receive credit for STAT 220 may not receive credit for IDTH 201

Schedule Details

Location Time Day(s)

Summer 2016 Courses

Summer 2016 Courses
Course - Section Title Days Time Location

Fall 2016 Courses

Fall 2016 Courses
Course - Section Title Days Time Location