Calculus & Its Applications

Larry Goldstein has received several distinguished teaching awards, given more than fifty Conference and Colloquium talks & addresses, and written more than fifty books in math and computer programming.  He received his PhD at Princeton and his BA and MA at the University of Pennsylvania. He also teaches part time at Drexel University.   David Schneider, who is known widely for his tutorial software, holds a BA degree from Oberlin College and a PhD from MIT.  He is currently an associate professor of mathematics at the University of Maryland. He has authored eight widely used math texts, fourteen highly acclaimed computer books, and three widely used mathematics software packages. He has also produced instructional videotapes at both the University of Maryland and the BBC.   Martha Siegel holds a BA from Russell Sage College, attended Rensselear Polytechnic Institute as a special student, and received his PhD at the University of Rochester. From 1966 until 1971 she taught at Goucher University in Baltimore. Since 1971 she has been a professor at Towson State University, also in Maryland. Professor Siegel has been on the writing team of this book since the fifth edition and is also the co-author of a precalculus reform book.

Preface

Introduction

 

0. Functions

0.1 Functions and Their Graphs

0.2 Some Important Functions

0.3 The Algebra of Functions

0.4 Zeros of Functions - The Quadratic Formula and Factoring

0.5 Exponents and Power Functions

0.6 Functions and Graphs in Applications

 

1. The Derivative

1.1 The Slope of a Straight Line

1.2 The Slope of a Curve at a Point

1.3 The Derivative

1.4 Limits and the Derivative

1.5 Differentiability and Continuity

1.6 Some Rules for Differentiation

1.7 More About Derivatives

1.8 The Derivative as a Rate of Change

 

2. Applications of the Derivative

2.1 Describing Graphs of Functions

2.2 The First and Second Derivative Rules

2.3 The First and Section Derivative Tests and Curve Sketching

2.4 Curve Sketching (Conclusion)

2.5 Optimization Problems

2.6 Further Optimization Problems

2.7 Applications of Derivatives to Business and Economics

 

3. Techniques of Differentiation

3.1 The Product and Quotient Rules

3.2 The Chain Rule and the General Power Rule

3.3 Implicit Differentiation and Related Rates

 

4. The Exponential and Natural Logarithm Functions

4.1 Exponential Functions

4.2 The Exponential Function ex

4.3 Differentiation of Exponential Functions

4.4 The Natural Logarithm Function

4.5 The Derivative of ln x

4.6 Properties of the Natural Logarithm Function

 

5. Applications of the Exponential and Natural Logarithm Functions

5.1 Exponential Growth and Decay

5.2 Compound Interest

5.3. Applications of the Natural Logarithm Function to Economics

5.4. Further Exponential Models

 

6. The Definite Integral

6.1 Antidifferentiation

6.2 The Definite Integral and Net Change of a Function

6.3 The Definite Integral and Area Under a Graph

6.4 Areas in the xy-plane

6.5 Applications of the Definite Integral

 

7. Functions of Several Variables

7.1 Examples of Functions of Several Variables

7.2 Partial Derivatives

7.3 Maxima and Minima of Functions of Several Variables

7.4 Lagrange Multipliers and Constrained Optimization

7.5 The Method of Least Squares

7.6 Double Integrals

 

8. The Trigonometric Functions

8.1 Radian Measure of Angles

8.2 The Sine and the Cosine

8.3 Differentiation and Integration of sin t and cos t

8.4 The Tangent and Other Trigonometric Functions

 

9. Techniques of Integration

9.1 Integration by Substitution

9.2 Integration by Parts

9.3 Evaluation of Definite Integrals

9.4 Approximation of Definite Integrals

9.5 Some Applications of the Integral

9.6 Improper Integrals

 

10. Differential Equations

10.1 Solutions of Differential Equations

10.2 Separation of Variables

10.3 First-Order Linear Differential Equations

10.4 Applications of First-Order Linear Differential Equations

10.5 Graphing Solutions of Differential Equations

10.6 Applications of Differential Equations

10.7 Numerical Solution of Differential Equations

 

11. Taylor Polynomials and Infinite Series

11.1 Taylor Polynomials

11.2 The Newton-Raphson Algorithm

11.3 Infinite Series

11.4 Series with Positive Terms

11.5 Taylor Series

 

12. Probability and Calculus

12.1 Discrete Random Variables

12.2 Continuous Random Variables

12.3 Expected Value and Variance

12.4 Exponential and Normal Random Variables

12.5 Poisson and Geometric Random Variables

 

Appendix: Areas under the Standard Normal Curve

Answers to Exercises

Index