Metropolitan State University

 My Plan for Fall 2017
 Wish List:  

Login to view your plan.

 Wait List:  

View/Modify Schedule  Registered:  Expand My Plan  
Remove from Wait List

< New Search Continue to Review My Plan >

MATH 340 - Mathematical Modeling
Fall 2017, Section 01

ID #Subj#SecTitleDatesDaysTimeCrdsStatusInstructorDelivery MethodLoc
000777 MATH 340 01 Mathematical Modeling
08/22 - 11/28
6:00pm - 9:20pm
4.0 Open Kaus, Cynthia
Location: z MnSCU Metropolitan State University
Building/Room: St Johns Hall L11

Meeting Details
8/22/2017 - 11/28/2017 T 6:00pm - 9:20pm St Johns Hall L11 Kaus, Cynthia

  • Prerequisites: For Applied Mathematics Majors: MATH 320 Probability AND MATH 315 Linear Algebra and Applications. Prerequisites: For Mathematics Teaching Majors: MATH 215 Discrete Mathematics, MATH 315 Linear Algebra and Applications, and STAT 201 Statistics I.

Location Details
Offered through: Metropolitan State University.
Campus: Metropolitan State University. Location: z MnSCU Metropolitan State University.

Seat Availability
Status: Open Size: 26 Enrolled: 24 Seats Remaining: 2

  • Requires minimum credits: 30

Full refund is available until August 27, 2017, 11:59PM CST.
Adding course is closed. Dropping course is closed.
The last day to withdraw from this course is November 20, 2017.

Tuition and Fees (Approximate)

Tuition and Fees (approximate):

Tuition -resident: $910.12
Tuition -nonresident: $1,856.92
Approximate Course Fees: $137.88

Course Level

General/Liberal Education Category
Upper Division Liberal Studies

Minnesota Transfer Curriculum Goal
Goal 04 - Mathematical/Logical Reasoning
  • Illustrate historical and contemporary applications of mathematical/logical systems.
  • Clearly express mathematical/logical ideas in writing.
  • Explain what constitutes a valid mathematical/logical argument(proof).
  • Apply higher-order problem-solving and/or modeling strategies.

Mathematical modeling is the investigation of real world phenomena using mathematical tools. This course includes topics such as dynamic and stochastic modeling (differential equations and discrete-time equations), as well as optimization modeling. Applications will include problems from such areas as the physical and biological sciences, business, and industry.

Add To Wait List