B.C.'s Energy College

MATH 106 - Calculus for Social Sciences II
Course Details
Course Code:
MATH 106

Credits:
3

Calendar Description:
Systems of linear equations, algebraic operations with matrices, determinants, introduction to linear programming, the theory, techniques and applications of integration, introduction to differential equations with emphasis to some special first-order equations and their applications to economics and social sciences.

Hours:
Total Hours: 60
Lecture Hours: 3
Seminars and Tutorials: 1

This course is offered online:
No

Pre-Requisites:
MATH 101 or MATH 105, i.e. a semester of differential calculus.

Co-Requisites:
None

Rearticulation Submission:
Yes

Course Content:
The Integral
- the antiderivative
- integration by substitution
- the definite integral
- area between curves
- the fundamental theorem of calculus
- numerical integration

Applications and Integration
- differential equations
- integration by parts
- using tables of integrals
- improper integrals
- probability density functions

Functions of Several Variables
- three-dimensional coordinate system
- partial derivatives
- maximum-minimum applications
- lagrange multipliers
- multiple integrals

Systems of Equations and Matrices
- systems of equations
- introduction to matrices
- Gauss-Jordan elimination
- inverse matrices
- Leontief models

Linear Programming
- systems of linear inequalities
- formulating linear programming models
- graphical solution of linear programming problems
- slack variables and the pivot
- maximization by the simplex method
- duality

Markov Chains and Decision Theory
- introduction to Markov chains
- regular Markov chains
- absorbing Markov chains
- expectation
- game theory
- m x n Matrix games

Learning Outcomes:
On successful completion of this course, the student will be able to:
- integrate single and multiple variable functions
- apply integration to problems in the social sciences
- solve differential equations
- find approximate solutions using numerical methods
- solve systems of linear equations using matrices and determinants
- do simple linear programming
- compute the probability of a simple event and apply integration to probability