Ph.D., M.S., University of Minnesota
B.A., Carleton College
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.
Course  Section  Title  Days  Time  Location 

Course  Section  Title  Days  Time  Location  

CISC 342  01  Computer AppExperimental Sci   T  R     1330  1510  OSS 415  
Description of course Genetics B/ Lab: 
CRN: 42467
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, analogsignal 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


STAT 220  04  Statistics I  M  W  F    0935  1040  OSS 329  
Description of course Genetics B/ Lab: 
CRN: 41052
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, chisquare, 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


STAT 220  05  Statistics I  M  W  F    1055  1200  OSS 329  
Description of course Genetics B/ Lab: 
CRN: 41053
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, chisquare, 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

Course  Section  Title  Days  Time  Location 
