Description: Introduction to probability, statistics, matrix and vector algebra  with emphasis on models and techniques relevant to the life sciences.

Prerequisites:

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.

Topics:

Descriptive Statistics

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

Matrix Algebra

Long-Term Dynamics or Equilibrium
Leslie Matrix Models and Eigenvalues

Probability

Probability of Events

Probability of Compound Events

Conditional Probability

Sequential 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.