Mark Werness portrait

Mark Werness

Associate Professor
Degree
Ph.D., M.S., University of Minnesota
B.A., Carleton College
Office
OSS 424
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.  

J-Term 2017 Courses

J-Term 2017 Courses
Course - Section Title Days Time Location

Spring 2017 Courses

Spring 2017 Courses
Course - Section Title Days Time Location
CISC 120 - 01 Computers in Elementary Educ M - W - F - - 1335 - 1440 OSS 429
CRN: 22365 4 Credit Hours Instructor: Mark E. Werness This course is intended for elementary education majors. Topics include the role of the computer in elementary and middle-school education, computer applications in science and mathematics, data analysis, software packages for use in elementary and middle-school classrooms, Computer-Assisted-Instruction (CAI), multimedia, electronic portfolios, telecommunication and software creation using tools such as MicroWorlds, Scratch, and HTML. This course fulfills the third course in the Natural Science and Mathematical and Quantitative Reasoning. Prerequisite: Elementary Education or SMEE major

Schedule Details

Location Time Day(s)
CISC 342 - 01 Computer App-Experimental Sci - - - - - - - -
CRN: 22845 4 Credit Hours Instructor: Mark E. Werness (Formerly QMCS 342) Introduction to the use of computers in the collection and analysis of scientific information. The course is designed to meet the needs of both natural science majors with an interest in scientific computing and computer science majors with an interest in laboratory science. Emphasis is placed on application of concepts and techniques in addition to LabVIEW programming. Topics include laboratory device interfacing, analog-signal acquisition and processing, frequency transformations, data analysis, image processing, and math modeling and simulation. Prerequisites: CISC 130 or 131; MATH 109 or 111 or 113; one course in a laboratory science

Schedule Details

Location Time Day(s)
STAT 220 - 04 Statistics I M - W - F - - 0935 - 1040 OSS 329
CRN: 20777 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)
STAT 220 - 05 Statistics I M - W - F - - 1055 - 1200 OSS 329
CRN: 20778 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)
STAT 460 - 01 Statistical Research/Practicum - - - - - - - -
CRN: 22770 4 Credit Hours Instructor: Mark E. Werness Students will work individually with the instructor to identify a statistical research topic of current interest or to identify a real practical problem, for which statistics can be used to produce a feasible solution. State and local governments, companies, businesses, TV channels, or even faculty doing research should be the natural source of real practical problems to be solved. For either the research or the practical problem, the final outcome should be a report with publication potential.

Schedule Details

Location Time Day(s)

Summer 2017 Courses

Summer 2017 Courses
Course - Section Title Days Time Location