Description: Introduction to probability, statistics, matrix and vector algebra with emphasis on models and techniques relevant to the life sciences.
A grade of C- or better in MATH115; or permission of department based on 3 ½ years of college preparatory mathematics (including trigonometry) and satisfactory performance on the Mathematics Placement Exam.
Basic Descriptive Statistics
Visual Display of Data
Bivariate Data and Linear Regression
Exponential and Logarithmic Functions
Discrete Time Modeling
Sequences and Discrete Difference Equations
Vectors and Matrices
Long-Term Dynamics or Equilibrium
Leslie Matrix Models and Eigenvalues
Probability of Events
Probability of Compound Events
Population Genetics Models
Learning Outcomes: After completing this course students should be able to demonstrate:
1. A mathematical understanding of biological data, including data collection, visualization/display, and analysis.
2. An understanding of discrete mathematical models of biological systems.
3. An understanding of key mathematical concepts relevant to life sciences including: discrete-time dynamics, vector and matrix operations, discrete probability.