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STAT: Statistics

313-01
Probability
 
MWF 12:15 pm - 1:20 pm
N. Dragovic
 
02/02 - 05/22
24/14/0
Lecture
CRN 21801
4 Cr.
Size: 24
Enrolled: 14
Waitlisted: 0
02/02 - 05/22
M T W Th F Sa Su

12:15 pm
1:20 pm
OSS 226

 

12:15 pm
1:20 pm
OSS 226

 

12:15 pm
1:20 pm
OSS 226

   

Subject: Statistics (STAT)

CRN: 21801

In Person | Lecture

St Paul: O'Shaughnessy Science Hall 226

  Natasa Dragovic

Probability theory in discrete and continuous sample spaces; random variables and distribution functions; moments; the moment-generating function; functions of random variables; law of large numbers; central limit theorem. Prerequisites: A grade of C- or above in MATH 200 (may be taken concurrently with consent of instructor). NOTE: Students who receive credit for STAT 313 may not receive credit for STAT 303.

4 Credits

314-01
Mathematical Statistics
 
MWF 9:35 am - 10:40 am
N. Clark
EdTrn 
02/02 - 05/22
24/14/0
Lecture
CRN 21802
4 Cr.
Size: 24
Enrolled: 14
Waitlisted: 0
02/02 - 05/22
M T W Th F Sa Su

9:35 am
10:40 am
BEC LL07

 

9:35 am
10:40 am
BEC LL07

 

9:35 am
10:40 am
BEC LL07

   

Subject: Statistics (STAT)

CRN: 21802

In Person | Lecture

St Paul: Brady Educational Center LL07

Requirements Met:
     School of Ed Transfer Course

  Nick Clark

Students will learn the theory and applications of point estimation, interval estimation, and hypothesis testing. Students will construct intervals and tests using a variety of statistical tools including frequentist statistical theory, Bayesian statistical theory, and resampling-based simulation. Prerequisites: Grades C- or higher in MATH 240 and STAT 313. NOTE: Students who receive credit for STAT 314 may not receive credit for STAT 303.

4 Credits

333-D01
Predictive Modeling
 
MWF 12:15 pm - 1:20 pm
N. Clark
EdTrnCore 
02/02 - 05/22
20/8/0
Lecture
CRN 21803
4 Cr.
Size: 20
Enrolled: 8
Waitlisted: 0
02/02 - 05/22
M T W Th F Sa Su

12:15 pm
1:20 pm
OSS 214

 

12:15 pm
1:20 pm
OSS 214

 

12:15 pm
1:20 pm
OSS 214

   

Subject: Statistics (STAT)

CRN: 21803

In Person | Lecture

St Paul: O'Shaughnessy Science Hall 214

Requirements Met:
     School of Ed Transfer Course
     Writing in the Discipline

  Nick Clark

The course introduces the theory and applications of simple and multiple regression methods, including model construction and selection, transformation of variables and residual analysis; introduction to GLM (generalized linear models) for categorical and count response variables; time series analysis with ARIMA (autoregressive integrated moving average models). Students are introduced to principles of data collection and analysis, learn to work with statistical literature. Students present a writing intensive small group course project. Prerequisites: Grades C- or higher in MATH 240 and in STAT 303 or STAT 314.

4 Credits

370-01
Bayesian Statistical Models
 
TR 1:30 pm - 3:10 pm
A. Shemyakin
 
02/02 - 05/22
20/19/0
Lecture
CRN 21804
4 Cr.
Size: 20
Enrolled: 19
Waitlisted: 0
02/02 - 05/22
M T W Th F Sa Su
 

1:30 pm
3:10 pm
OSS 214

 

1:30 pm
3:10 pm
OSS 214

     

Subject: Statistics (STAT)

CRN: 21804

In Person | Lecture

St Paul: O'Shaughnessy Science Hall 214

  Arkady Shemyakin

The course covers a range of statistical models used in applications including Actuarial Science, Finance, Health, and Social Sciences. It is oriented towards practical model construction and problem solving. The theory of Monte Carlo and Markov Chain Monte Carlo simulation is considered as well as its practical implementation. Credibility theory serves as one of the major applications. Prerequisites: MATH 109, 112 or 113; AND STAT 314 or DASC 240.

4 Credits

460-01
STAT & Data Science Practicum
 
TR 3:25 pm - 5:00 pm
A. Shemyakin
Core 
02/02 - 05/22
20/20/4
Lecture
CRN 21805
4 Cr.
Size: 20
Enrolled: 20
Waitlisted: 4
02/02 - 05/22
M T W Th F Sa Su
 

3:25 pm
5:00 pm
OSS 214

 

3:25 pm
5:00 pm
OSS 214

     

Subject: Statistics (STAT)

CRN: 21805

In Person | Lecture

St Paul: O'Shaughnessy Science Hall 214

Requirements Met:
     [Core] Signature Work

  Arkady Shemyakin

This course provides students the opportunity to develop and pursue an advanced statistical analysis with real world relevance and application. In addition to working with a faculty instructor, students are also given the opportunity to collaborate with professional mentors from various industries and to participate in national competitions. Previous sponsors include the Minnesota Department of Natural Resources, the Travelers Companies, U.S. Bancorp, SCOR Reinsurance, Drake Bank, and numerous professors from other departments at St. Thomas. Grade of C- or higher in STAT 360 and senior standing.

4 Credits


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