Montgomery College 2018-2019 Catalog 
    
    Dec 04, 2022  
Montgomery College 2018-2019 Catalog [ARCHIVED CATALOG]

Add to Favorites (opens a new window)

MATH 171 - Calculus for Life Sciences II


A continuation of MATH 170 ; intended primarily for students of the life sciences.  Topics include: integration, partial derivatives, systems of linear equations, normal and binomial distributions, sampling distributions, an introduction to differential equations, and discrete dynamical systems. Alongside the mathematical concepts will be applications to the life sciences. Not intended for students of the physical sciences, engineering, or mathematics. PREREQUISITE(S): A grade of C or better in MATH 170  or MATH 181 . Assessment Level(s): ENGL 101 /ENGL 101A , READ 120  For computation of tuition, this course is equivalent to five semester hours. Five hours each week.

4 semester hours

MATH 171 is NOT a substitute for MATH 182

Course Outcomes:
Upon completion of this course a student will be able to:

  • Integration
  • Approximate definite integrals by using appropriate numerical techniques.
  • Evaluate integrals using integration by parts.
  • Evaluate improper integrals.
  • Linear Algebra
  • Determine the solution to a linear system.
  • Perform matrix calculations by applying the rules of matrix algebra.
  • Produce eigenvalues and associated eigenvectors for a given matrix.
  • Multivariable Calculus
  • Use partial derivatives to model and analyze applications involving optimization.
  • Set up and compute double integrals.
  • Differential Equations
  • Solve first-order separable and linear differential equations and corresponding initial-value problems.
  • Use Euler’s Method to approximate solutions to differential equations.
  • Analyze linear and nonlinear systems of differential equations.
  • Probability
  • Set up and evaluate appropriate expressions for discrete (including binomial) and continuous (uniform, exponential and normal) random variables.
  • Use the results of the Central Limit Theorem to predict long-term patterns of variation based on an understanding of the normal distribution.
  • Discrete Dynamical Systems
  • Using sequences and cobwebbing for population models, determine the stability of the equilibrium points.
  • Applications
  • Use the methods learned in this course to solve and understand applied problems in the life sciences.
     


View Schedule of Classes




Add to Favorites (opens a new window)