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MATH 230 - Introduction to Mathematical Modeling
Fall 2019, Section 01

search actionsID #Subj#SecTitleDatesDaysTimeCrdsStatusInstructorDelivery MethodLoc
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001086 MATH 230 01 Introduction to Mathematical Modeling
08/29 - 10/10
Th
6:00pm - 9:20pm
2.0 Open Wagstrom, Rikki
Location: z MnSCU Metropolitan State University
Building/Room: LIBRARY 321


Meeting Details
DatesDaysTimeBuilding/RoomInstructor
8/29/2019 - 10/10/2019 Th 6:00pm - 9:20pm LIBRARY 321 Wagstrom, Rikki

Notes
  • Note: Students whose prerequisites are not identified by the system would contact the Math and Statistics department for an override at MATH@metrostate.edu. First day attendance required except by instructor permission. First day attendance required except by instructor permission.

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

Seat Availability
Status: Open Size: 26 Enrolled: 23 Seats Remaining: 3

Prerequisites (Courses and Tests)
This course requires both of these prerequisites
MATH 211 - Calculus II
STAT 201 - Statistics I

Restrictions
  • Permission is required

Add/Drop/Withdraw
Full refund is available until August 30, 2019, 11:59PM CST.
Adding course is closed. Dropping course is closed.
The last day to withdraw from this course is October 3, 2019.

Tuition and Fees (Approximate)

Tuition and Fees (approximate):

Tuition -resident: $468.72
Tuition -nonresident: $956.32
Approximate Course Fees: $72.22

Course Level
Undergraduate

Description
Mathematical modeling is the process of using mathematics and computational tools to gain insights into complex problems arising in the sciences, business, industry, and society. Mathematical modeling is an iterative process which involves a computational approach to the scientific method. Assumptions are established, a mathematical structure consistent with those assumptions is developed, hypotheses are produced and tested against empirical evidence, and then the model is refined accordingly. The quality of these models is examined as part of the verification process, and the entire cycle repeats as improvements and adjustments to the model are made. This course provides an introduction to both the mathematical modeling process as well as deterministic and stochastic methods that are commonly employed to investigate time-dependent phenomena.

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