Mark Werness portrait

Mark Werness

Associate Professor, Statistics Program Director
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.  

Fall 2018 Courses

Fall 2018 Courses
Course - Section Title Days Time Location
STAT 220 - 01 Statistics I M - W - F - - 0935 - 1040 JRC 126

Days of Week:

M - W - F - -

Time of Day:

0935 - 1040

Location:

JRC 126

Course Registration Number:

40825 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Mark E. Werness

NOTE: Students registering for lecture STAT 220 01 must also register for lab 51, 52, or 53. Formerly IDTH 220. Statistics I is composed of an in-depth study of the processes through which statistics are applied in order to learn about environments and events. In this course, there is an intensive focus on the application, analysis, interpretation, and presentation of both descriptive and inferential statistics in myriad contexts. Topics covered include analytical and graphical tools for summarizing categorical and quantitative variables; correlation and simple linear regression; sampling strategies and research design; probability, probability models, and random variables; sampling distribution models; inference for one and two proportions; inference for one and two or more independent means; inference for paired means; inference for comparing counts; and inference for simple linear regression. Students must enroll in both a lecture section and software-specific laboratory section, in the same academic semester, to successfully complete STAT 220. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at MATH 108 or above; or MATH 100, 101, or 105. NOTE: Students who receive credit for STAT 220 may not receive credit for STAT 201.

Schedule Details

Location Time Day(s)
STAT 220 - 02 Statistics I M - W - F - - 1055 - 1200 JRC 126

Days of Week:

M - W - F - -

Time of Day:

1055 - 1200

Location:

JRC 126

Course Registration Number:

41939 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Mark E. Werness

NOTE: Students registering for lecture STAT 220 02 must also register for lab 54, 55, or 56. Formerly IDTH 220. Statistics I is composed of an in-depth study of the processes through which statistics are applied in order to learn about environments and events. In this course, there is an intensive focus on the application, analysis, interpretation, and presentation of both descriptive and inferential statistics in myriad contexts. Topics covered include analytical and graphical tools for summarizing categorical and quantitative variables; correlation and simple linear regression; sampling strategies and research design; probability, probability models, and random variables; sampling distribution models; inference for one and two proportions; inference for one and two or more independent means; inference for paired means; inference for comparing counts; and inference for simple linear regression. Students must enroll in both a lecture section and software-specific laboratory section, in the same academic semester, to successfully complete STAT 220. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at MATH 108 or above; or MATH 100, 101, or 105. NOTE: Students who receive credit for STAT 220 may not receive credit for STAT 201.

Schedule Details

Location Time Day(s)
STAT 400 - 01 Data Mining & Machine Learning M - W - - - - 1335 - 1510 OSS 429

Days of Week:

M - W - - - -

Time of Day:

1335 - 1510

Location:

OSS 429

Course Registration Number:

42006 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Mark E. Werness

(Formerly IDTH 400) Introduction to statistical learning methods, from a statistical and computational perspective, to deal with massive and complex data. Topics include: Introduction; creating a project and diagram. Data preparation; defining and exploring data sources. Pattern discovery; cluster analysis, market basket analysis. Decision trees; cultivating and pruning decision trees, autonomous tree growth. Regression; transforming inputs, categorical inputs, polynomial regression. Neural Networks; input selection, stopped training. Model assessment; fit statistics, graphs, separate sampling. Model implementation; scored data sets, score code models. Applications. This course will give the basic ideas and intuition behind these methods, and special emphasis will be placed on their application through statistical software. Prerequisites: CISC 130 or 131, and MATH 113, and STAT 320 or 333.

Schedule Details

Location Time Day(s)

J-Term 2019 Courses

J-Term 2019 Courses
Course - Section Title Days Time Location

Spring 2019 Courses

Spring 2019 Courses
Course - Section Title Days Time Location
CISC 120 - 01 Computers in Elementary Educ M - W - - - - 1525 - 1700 OSS 415

Days of Week:

M - W - - - -

Time of Day:

1525 - 1700

Location:

OSS 415

Course Registration Number:

22869 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Lisa M. Rezac, 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 440 - 01 Artfcl Intelligence & Robotics M - W - - - - 1335 - 1510 OSS 415

Days of Week:

M - W - - - -

Time of Day:

1335 - 1510

Location:

OSS 415

Course Registration Number:

21563 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Mark E. Werness

(Formerly QMCS 380) Theory and implementation techniques using computers to solve problems, play games, prove theorems, recognize patterns, create artwork and musical scores, translate languages, read handwriting, speak and perform mechanical assembly. Emphasis placed on implementation of these techniques in robots. Prerequisites: A C- in CISC 230 and STAT 220 (IDTH 220)

Schedule Details

Location Time Day(s)
STAT 220 - 01 Statistics I M - W - F - - 0935 - 1040 JRC 126

Days of Week:

M - W - F - -

Time of Day:

0935 - 1040

Location:

JRC 126

Course Registration Number:

20638 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Mark E. Werness

NOTE: Students registering for lecture STAT 220 01 must also register for lab 51, 52, or 53. Formerly IDTH 220. Statistics I is composed of an in-depth study of the processes through which statistics are applied in order to learn about environments and events. In this course, there is an intensive focus on the application, analysis, interpretation, and presentation of both descriptive and inferential statistics in myriad contexts. Topics covered include analytical and graphical tools for summarizing categorical and quantitative variables; correlation and simple linear regression; sampling strategies and research design; probability, probability models, and random variables; sampling distribution models; inference for one and two proportions; inference for one and two or more independent means; inference for paired means; inference for comparing counts; and inference for simple linear regression. Students must enroll in both a lecture section and software-specific laboratory section, in the same academic semester, to successfully complete STAT 220. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at MATH 108 or above; or MATH 100, 101, or 105. NOTE: Students who receive credit for STAT 220 may not receive credit for STAT 201.

Schedule Details

Location Time Day(s)
STAT 220 - 02 Statistics I M - W - F - - 1055 - 1200 JRC 126

Days of Week:

M - W - F - -

Time of Day:

1055 - 1200

Location:

JRC 126

Course Registration Number:

20639 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Mark E. Werness

NOTE: Students registering for lecture STAT 220 02 must also register for lab 54, 55, or 56. Formerly IDTH 220. Statistics I is composed of an in-depth study of the processes through which statistics are applied in order to learn about environments and events. In this course, there is an intensive focus on the application, analysis, interpretation, and presentation of both descriptive and inferential statistics in myriad contexts. Topics covered include analytical and graphical tools for summarizing categorical and quantitative variables; correlation and simple linear regression; sampling strategies and research design; probability, probability models, and random variables; sampling distribution models; inference for one and two proportions; inference for one and two or more independent means; inference for paired means; inference for comparing counts; and inference for simple linear regression. Students must enroll in both a lecture section and software-specific laboratory section, in the same academic semester, to successfully complete STAT 220. This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum. Prerequisites: Math placement at MATH 108 or above; or MATH 100, 101, or 105. NOTE: Students who receive credit for STAT 220 may not receive credit for STAT 201.

Schedule Details

Location Time Day(s)