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
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.  

Summer 2014 Courses

Summer 2014 Courses
Course - Section Title Days Time Location

Fall 2014 Courses

Fall 2014 Courses
Course - Section Title Days Time Location
CISC 321 - 01 Systems Analysis and Design II - T - R - 1525 - 1700 OSS 428
CRN: 40843 4 Credit Hours (Formerly QMCS 421) Continuation of CISC 320. Concentration on user-centered design (UCD), physical design, low- and high- fidelity prototyping, and agile methods. Emphasis on managerial problems in systems development. Continued use of CASE and project-management tools. A "real world" design and prototyping project is an integral part of this course. Prerequisite: CISC 320
STAT 220 - 04 Statistics I M - W - F 0935 - 1040 OEC 206
CRN: 41142 4 Credit Hours 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
STAT 220 - 05 Statistics I M - W - F 1055 - 1200 OEC 206
CRN: 41143 4 Credit Hours 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

J-Term 2015 Courses

J-Term 2015 Courses
Course - Section Title Days Time Location