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Digital file of Calculus for Biology and Medicine for sale

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Category : Higher Education

Calculus for Biology and Medicine by Claudia Neuhauser, University of Minnesota ZIP OR PDF for sale 

Table of Contents

1. Preview and Review.

Preliminaries. Elementary Functions. Graphing. Review Problems.

2. Limits and Continuity.

Limits. Continuity. The Sandwich Theorem and Some Trigonometric Limits. Limits at Infinity. Continuity.

3. Differentiation.

Formal Definition of the Derivative. The Power Rule, the Basic Rules of Differentiation, and the Derivatives of Polynomials. The Product and Quotient Rules, and the Derivatives of Rational and Power Functions. The Chain Rule and Higher Derivatives. Derivatives of Trigonometric Functions. Derivatives of Exponential Functions. Derivatives of Inverse and Logarithmic Functions. Approximation and Local Linearity.

4. Applications of Differentiation.

Local Extrema and the Mean Value Theorem. Monotonicity and Concavity. Extrema, Inflection Points and Graphing. Optimization. L'Hospital's Rule. Numerical Methods. Antiderivatives. Review Problems.

5. Integration.

The Definite Integral. The Fundamental Theorem of Calculus. Applications of Integration.

6. Integration Techniques and Computational Methods.

The Substitution Rule. Integration by Parts. Improper Integrals. Numerical Integration. Tables of Integration. The Taylor Approximation.

7. Differential Equations.

Solving Differential Equations. Equilibria and Their Stability. Systems of Autonomous Equations.

8. Applications of Integration.

Rectification of Curves. Densities and Histograms. Average Values. The Normal Distribution. Age-Structured Populations.

9. Linear Algebra and Analytic Geometry.

Linear Systems. Matrices. Linear Maps, Eigenvectors and Eignvalues. Analytic Geometry.

10. Multivariable Calculus.

Functions of Two or More Independent Variables. Limits and Continuity. Partial Derivatives. Tangent Planes, Differentiability, and Linearization. More About Derivatives.

11. Systems of Differential Equations.

Linear Systems—Theory. Linear Systems—Applications. Nonlinear Autonomous Systems—Theory. Nonlinear Systems—Applications.

12. Probability and Statistics.

Counting. What Is Probability? Conditional Probability and Independence. Discrete Random Variables and Discrete Distributions. Continuous Distributions. Statistical Tools.

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