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DASC: Data Science

460-01
STAT & Data Science Practicum
 
TR 3:25 pm - 5:00 pm
TBD
Core 
02/01 - 05/21
24/0/0
Lecture
CRN 22148
4 Cr.
Size: 24
Enrolled: 0
Waitlisted: 0
02/01 - 05/21
M T W Th F Sa Su
 

3:25 pm
5:00 pm
In Person

 

3:25 pm
5:00 pm
In Person

     

Subject: Data Science (DASC)

CRN: 22148

Lecture

St Paul: In Person

Requirements Met:
     [Core] Signature Work

Instructor: TBD

This course provides students the opportunity to develop and pursue an advanced statistical data 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. Prerequisites: Grade of C- or higher in DASC 360 and senior standing.

4 Credits

STAT: Statistics

🔗 Allied courses: STAT Major

303-01
Statistics/Applied Sciences
 
TR 1:30 pm - 3:10 pm
A. Shemyakin
 
02/01 - 05/21
24/0/0
Lecture
CRN 21578
4 Cr.
Size: 24
Enrolled: 0
Waitlisted: 0
02/01 - 05/21
M T W Th F Sa Su
 

1:30 pm
3:10 pm
OSS 226

 

1:30 pm
3:10 pm
OSS 226

     

Subject: Statistics (STAT)

CRN: 21578

In Person | Lecture

St Paul: O'Shaughnessy Science Hall 226

  Arkady Shemyakin

Probability, Estimation, Hypothesis Testing, Analysis of Variance, Regression Analysis, Topics selected from Experimental Design, Statistical Process Control, Non-Parametric Methods, Factor Analysis as time permits. Prerequisite: A grade of C- or above in MATH 114. NOTE: Students who receive credit for STAT 303 may not receive credit for STAT 313 or STAT 314.

4 Credits

313-01
Probability
 
TR 8:00 am - 9:40 am
N. Dragovic
 
02/01 - 05/21
24/0/0
Lecture
CRN 21579
4 Cr.
Size: 24
Enrolled: 0
Waitlisted: 0
02/01 - 05/21
M T W Th F Sa Su
 

8:00 am
9:40 am
OWS 257

 

8:00 am
9:40 am
OWS 257

     

Subject: Statistics (STAT)

CRN: 21579

In Person | Lecture

St Paul: Owens Science Hall 257

  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 12:15 pm - 1:20 pm
N. Clark
EdTrn 
02/01 - 05/21
24/0/0
Lecture
CRN 21580
4 Cr.
Size: 24
Enrolled: 0
Waitlisted: 0
02/01 - 05/21
M T W Th F Sa Su

12:15 pm
1:20 pm
OSS 127

 

12:15 pm
1:20 pm
OSS 127

 

12:15 pm
1:20 pm
OSS 127

   

Subject: Statistics (STAT)

CRN: 21580

In Person | Lecture

St Paul: O'Shaughnessy Science Hall 127

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

333-01
Predictive Modeling
 
MWF 10:55 am - 12:00 pm
N. Clark
EdTrn 
02/01 - 05/21
20/0/0
Lecture
CRN 21581
4 Cr.
Size: 20
Enrolled: 0
Waitlisted: 0
02/01 - 05/21
M T W Th F Sa Su

10:55 am
12:00 pm
OSS 127

 

10:55 am
12:00 pm
OSS 127

 

10:55 am
12:00 pm
OSS 127

   

Subject: Statistics (STAT)

CRN: 21581

In Person | Lecture

St Paul: O'Shaughnessy Science Hall 127

Requirements Met:
     School of Ed Transfer Course

  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

460-01
STAT & Data Science Practicum
 
TR 3:25 pm - 5:00 pm
A. Shemyakin
Core 
02/01 - 05/21
24/0/0
Lecture
CRN 21582
4 Cr.
Size: 24
Enrolled: 0
Waitlisted: 0
02/01 - 05/21
M T W Th F Sa Su
 

3:25 pm
5:00 pm
OSS 226

 

3:25 pm
5:00 pm
OSS 226

     

Subject: Statistics (STAT)

CRN: 21582

In Person | Lecture

St Paul: O'Shaughnessy Science Hall 226

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

490-01
Topics
 
MW 3:25 pm - 5:00 pm
N. Clark
 
02/01 - 05/21
20/0/0
Lecture
CRN 22150
4 Cr.
Size: 20
Enrolled: 0
Waitlisted: 0
02/01 - 05/21
M T W Th F Sa Su

3:25 pm
5:00 pm
OSS 227

 

3:25 pm
5:00 pm
OSS 227

       

Subject: Statistics (STAT)

CRN: 22150

In Person | Lecture

St Paul: O'Shaughnessy Science Hall 227

  Nick Clark

The subject matter of these courses will vary from year to year, but will not duplicate existing courses. Descriptions of these courses are available in Classfinder, View Searchable Class Schedule

4 Credits


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