Sergey Berg portrait

Sergey Berg

Assistant Professor
Degree
Ph.D., 2016, Conservation Biology, University of Minnesota
B.S., 2011, Wildlife Management, University of Minnesota
B.S., 2010, Aerospace Engineering (Astrophysics Minor), University of Minnesota
Office
OSS 414
Phone
(651) 962-5382

Fall 2018 Courses

Fall 2018 Courses
Course - Section Title Days Time Location
STAT 220 - 03 Statistics I - T - R - - - 0955 - 1135 OWS 150

Days of Week:

- T - R - - -

Time of Day:

0955 - 1135

Location:

OWS 150

Course Registration Number:

40826 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Sergey S. Berg

NOTE: Students registering for lecture STAT 220 03 must also register for lab 57, 58, or 59. 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 460 - 02 Statistical Research/Practicum - - - - - - - -

Days of Week:

- - - - - - -

Time of Day:

-

Location:

Course Registration Number:

42263 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Sergey S. Berg

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)

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
STAT 220 - 04 Statistics I - T - R - - - 1330 - 1510 OWS 150

Days of Week:

- T - R - - -

Time of Day:

1330 - 1510

Location:

OWS 150

Course Registration Number:

20641 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Sergey S. Berg

NOTE: Students registering for lecture STAT 220 04 must also register for lab 60, 61, or 62. 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 - 05 Statistics I - T - R - - - 1525 - 1700 OWS 150

Days of Week:

- T - R - - -

Time of Day:

1525 - 1700

Location:

OWS 150

Course Registration Number:

20642 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Sergey S. Berg

NOTE: Students registering for lecture STAT 220 05 must also register for lab 63, 64, or 65. 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 320 - D01 Statistics II - T - R - - - 0955 - 1135 OSS 429

Days of Week:

- T - R - - -

Time of Day:

0955 - 1135

Location:

OSS 429

Course Registration Number:

22362 (View in ClassFinder)

Credit Hours:

4 Credit Hours

Instructor:

Sergey S. Berg

Applied linear regression models. Simple linear regression; introduction, inferences, diagnostics, remedial measures, simultaneous inference. Matrix approach in linear regression. Multiple regression; inference, remedial measures, extra sums of squares, partial determinations, standardized models, use of indicator and mixed variables, polynomial regression, model selection and validation, diagnostics, remedial measures, multicollinearity and effects, autocorrelation. Single and multi-factor analysis of variance: analysis of factor level means, interactions, inferences, diagnostics and remedial measures. A statistical package must be used as tool. Optional topics may include: logistic regression, design of experiments, and forecasting. Prerequisite: One of the following, STAT 201, STAT 220, STAT 333, MATH 303

Schedule Details

Location Time Day(s)