Calculus for Biology and Medicine, 4th edition

Published by Pearson (August 1, 2021) © 2017

  • Claudia Neuhauser University of Minnesota
  • Marcus Roper University of California at Los Angeles
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For one-semester or two-semester courses in Calculus for Life Sciences.

Shows students how calculus is used to analyze phenomena in nature—while providing flexibility for instructors to teach at their desired level of rigor

Calculus for Biology and Medicine motivates life and health science majors to learn calculus through relevant and strategically placed applications to their chosen fields. It presents the calculus in such a way that the level of rigor can be adjusted to meet the specific needs of the audience, from a purely applied course to one that matches the rigor of the standard calculus track.  


In the 4th Edition, new co-author Marcus Roper (UCLA) partners with author Claudia Neuhauser to preserve these strengths while adding an unprecedented number of real applications and infusing more modeling and technology.

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(NOTE: Each chapter concludes with Key Terms and Review Problems.)

1. Preview and Review

  • 1.1 Precalculus Skills Diagnostic Test
  • 1.2 Preliminaries
  • 1.3 Elementary Functions
  • 1.4 Graphing

2. Discrete-Time Models, Sequences, and Difference Equations

  • 2.1 Exponential Growth and Decay
  • 2.2 Sequences
  • 2.3 Modeling with Recurrence Equations

3. Limits and Continuity

  • 3.1 Limits
  • 3.2 Continuity
  • 3.3 Limits at Infinity
  • 3.4 Trigonometric Limits and the Sandwich Theorem
  • 3.5 Properties of Continuous Functions
  • 3.6 A Formal Definition of Limits (Optional)

4. Differentiation

  • 4.1 Formal Definition of the Derivative
  • 4.2 Properties of the Derivative
  • 4.3 Power Rules and Basic Rules
  • 4.4 The Product and Quotient Rules, and the Derivatives of Rational and Power Functions
  • 4.5 Chain Rule
  • 4.6 Implicit Functions and Implicit Differentiation
  • 4.7 Higher Derivatives
  • 4.8 Derivatives of Trigonometric Functions
  • 4.9 Derivatives of Exponential Functions
  • 4.10 Inverse Functions and Logarithms
  • 4.11 Linear Approximation and Error Propagation

5. Applications of Differentiation

  • 5.1 Extrema and the Mean-Value Theorem
  • 5.2 Monotonicity and Concavity
  • 5.3 Extrema and Inflection Points
  • 5.4 Optimization
  • 5.5 L'Hôpital's Rule
  • 5.6 Graphing and Asymptotes
  • 5.7 Recurrence Equations: Stability (Optional)
  • 5.8 Numerical Methods: The Newton - Raphson Method (Optional)
  • 5.9 Modeling Biological Systems Using Differential Equations (Optional)
  • 5.10 Antiderivatives

6. Integration

  • 6.1 The Definite Integral
  • 6.2 The Fundamental Theorem of Calculus
  • 6.3 Applications of Integration

7. Integration Techniques and Computational Methods

  • 7.1 The Substitution Rule
  • 7.2 Integration by Parts and Practicing Integration
  • 7.3 Rational Functions and Partial Fractions
  • 7.4 Improper Integrals (Optional)
  • 7.5 Numerical Integration
  • 7.6 The Taylor Approximation (optional)
  • 7.7 Tables of Integrals (Optional)

8. Differential Equations

  • 8.1 Solving Separable Differential Equations
  • 8.2 Equilibria and Their Stability
  • 8.3 Differential Equation Models
  • 8.4 Integrating Factors and Two-Compartment Models

9. Linear Algebra and Analytic Geometry

  • 9.1 Linear Systems
  • 9.2 Matrices
  • 9.3 Linear Maps, Eigenvectors, and Eigenvalues
  • 9.4 Demographic Modeling
  • 9.5 Analytic Geometry

10. Multivariable Calculus

  • 10.1 Two or More Independent Variables
  • 10.2 Limits and Continuity (optional)
  • 10.3 Partial Derivatives
  • 10.4 Tangent Planes, Differentiability, and Linearization
  • 10.5 The Chain Rule and Implicit Differentiation (Optional)
  • 10.6 Directional Derivatives and Gradient Vectors (Optional)
  • 10.7 Maximization and Minimization of Functions (Optional)
  • 10.8 Diffusion (Optional)
  • 10.9 Systems of Difference Equations (Optional)

11. Systems of Differential Equations

  • 11.1 Linear Systems: Theory
  • 11.2 Linear Systems: Applications
  • 11.3 Nonlinear Autonomous Systems: Theory
  • 11.4 Nonlinear Systems: Lotka - Volterra Model of Interspecific Interactions
  • 11.5 More Mathematical Models (Optional)

12. Probability and Statistics

  • 12.1 Counting
  • 12.2 What Is Probability?
  • 12.3 Conditional Probability and Independence
  • 12.4 Discrete Random Variables and Discrete Distributions
  • 12.5 Continuous Distributions
  • 12.6 Limit Theorems
  • 12.7 Statistical Tools

Appendices

  • A: Frequently Used Symbols
  • B: Table of the Standard Normal Distribution

Answers to Odd-Numbered Problems

References

Photo Credits

Index

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