# Sergey Berg

Limited-Term Faculty
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

## Spring 2018 Courses

Spring 2018 Courses
Course - Section Title Days Time Location
STAT 220 - 06 Statistics I M - W - - - - 1335 - 1510 OSS 432

M - W - - - -

1335 - 1510

OSS 432

### Course Registration Number:

20708 (View in ClassFinder)

4 Credit Hours

### Instructor:

Sergey S. Berg

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 - 12 Statistics I - T - R - - - 0955 - 1135 OSS 329

- T - R - - -

0955 - 1135

OSS 329

### Course Registration Number:

20714 (View in ClassFinder)

4 Credit Hours

### Instructor:

Sergey S. Berg

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 - 13 Statistics I - T - R - - - 1330 - 1510 OSS 329

- T - R - - -

1330 - 1510

OSS 329

### Course Registration Number:

20715 (View in ClassFinder)

4 Credit Hours

### Instructor:

Sergey S. Berg

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 360 - 01 Advanced Statistical Software - T - R - - - 1525 - 1700 OSS 429

- T - R - - -

1525 - 1700

OSS 429

### Course Registration Number:

22277 (View in ClassFinder)

4 Credit Hours

### Instructor:

Sergey S. Berg

(Formerly IDTH 360) This course introduces students to an advanced statistical software package to effectively apply statistical methods, in general. Students create data sets from raw data files, create variables within a data set, append and/or modify data sets, create subsets, then apply a whole host of statistical procedures, create graphs and produce reports. The course will be based on several leading advanced statistical software packages, which will be chosen from semester to semester to match the needs of the community. Prerequisites: STAT 220 or STAT 314

## Schedule Details

Location Time Day(s)
STAT 460 - 02 Statistical Research/Practicum - - - - - - - -

- - - - - - -

-

### Course Registration Number:

22931 (View in ClassFinder)

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)

## Summer 2018 Courses

Summer 2018 Courses
Course - Section Title Days Time Location

## Fall 2018 Courses

Fall 2018 Courses
Course - Section Title Days Time Location
STAT 220 - 04 Statistics I - T - R - - - 1330 - 1510 OWS 150

- T - R - - -

1330 - 1510

OWS 150

### Course Registration Number:

40827 (View in ClassFinder)

4 Credit Hours

### Instructor:

Sergey S. Berg

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 - T - R - - - 1525 - 1700 OWS 150

- T - R - - -

1525 - 1700

OWS 150

### Course Registration Number:

40828 (View in ClassFinder)

4 Credit Hours

### Instructor:

Sergey S. Berg

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 320 - D01 Statistics II - T - R - - - 0955 - 1135 OSS 431

- T - R - - -

0955 - 1135

OSS 431

### Course Registration Number:

41725 (View in ClassFinder)

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 333

## Schedule Details

Location Time Day(s)