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Finite Mathematics and Calculus with Applications / Edition 9

Finite Mathematics and Calculus with Applications / Edition 9

by Margaret L. Lial


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Finite Mathematics and Calculus with Applications / Edition 9

Finite Mathematics and Calculus with Applications, Tenth Edition by Lial, Greenwell, and Ritchey, is our most applied text to date, making the math relevant and accessible for students of business, life science, and social sciences. Current applications, many using real data, are incorporated in numerous forms throughout the book, preparing students for success in their professional careers. With this edition, students will find new ways to help them learn the material, such as Warm-Up Exercises and added “help text” within examples.

NOTE: Before purchasing, check with your instructor to ensure you select the correct ISBN. Several versions of Pearson's MyLab & Mastering products exist for each title, and registrations are not transferable. To register for and use Pearson's MyLab & Mastering products, you may also need a Course ID, which your instructor will provide.

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Product Details

ISBN-13: 2900321749085
Publisher: Pearson
Publication date: 11/18/2011
Edition description: Older Edition
Pages: 1136
Product dimensions: 6.50(w) x 1.50(h) x 9.50(d)

About the Author

Marge Lial (late) was always interested in math; it was her favorite subject in the first grade! Marge's intense desire to educate both her students and herself has inspired the writing of numerous best-selling textbooks. Marge, who received bachelor's and master's degrees from California State University at Sacramento, was affiliated with American River College. An avid reader and traveler, her travel experiences often found their way into her books as applications, exercise sets, and feature sets. Her interest in archeology lead to trips to various digs and ruin sites, producing some fascinating problems for her textbooks involving such topics as the building of Mayan pyramids and the acoustics of ancient ball courts in the Yucatan.

Raymond N. Greenwell earned a B.A. in Mathematics and Physics from the University of San Diego, and an M.S. in Statistics, an M.S. in Applied Mathematics, and a Ph.D. in Applied Mathematics from Michigan State University, where he earned the graduate student teaching award in 1979. After teaching at Albion College in Michigan for four years, he moved to Hofstra University in 1983, where he currently is Professor of Mathematics.

Raymond has published articles on fluid mechanics, mathematical biology, genetic algorithms, combinatorics, statistics, and undergraduate mathematics education. He is a member of MAA, AMS, SIAM, NCTM, and AMATYC. He has served as governor of the Metropolitan New York Section of the MAA, as well as webmaster and liaison coordinator, and he received a distinguished service award from the Section in 2003. He is an outdoor enthusiast and leads trips in the Sierra Club’s Inner City Outings program.

Nathan P. Ritchey earned a B.A. in Mathematics with a minor in Music from Mansfield University of Pennsylvania. He earned a M.S. in Applied Mathematics and a Ph.D. in Mathematics from Carnegie Mellon University. He is former chair of the Department of Mathematics and Statistics at Youngstown State University and is currently serving as the dean of the College of Science and Health Professions at Edinboro University. He has published articles in economics, honors education, medicine, mathematics, operations research, and student recruitment. Nate is a Consultant/Evaluator for the North Central Association's Higher Learning Commission and regularly participates in program evaluations.

In recognition of his numerous activities, Nate has received the Distinguished Professor Award for University Service, the Youngstown Vindicator's "People Who Make a Difference Award," the Watson Merit Award for Department Chairs, the Spirit in Education Award from the SunTex corporation, and the Provost's Merit Award for significant contributions to the Honors Program.

Table of Contents

R. Algebra Reference.
R.1 Polynomials.
R.2 Factoring.
R.3 Rational Expressions.
R.4 Equations.
R.5 Inequalities.
R.6 Exponents.
R.7 Radicals.

1. Linear Functions.
1.1 Slopes and Equations of Lines.
1.2 Linear Functions and Applications.
1.3 The Least Squares Line.

2. Systems of Linear Equations and Matrices.
2.1 Solution of Linear Systems by the Echelon Method.
2.2 Solution of Linear Systems by the Gauss-Jordan Method.
2.3 Addition and Subtraction of Matrices.
2.4 Multiplication of Matrices.
2.5 Matrix Inverses.
2.6 Input-Output Models.

3. Linear Programming: The Graphical Method.
3.1 Graphing Linear Inequalities.
3.2 Solving Linear Programming Problems Graphically.
3.3 Applications of Linear Programming.

4. Linear Programming: The Simplex Method.
4.1 Slack Variables and the Pivot.
4.2 Maximization Problems.
4.3 Minimization Problems; Duality.
4.4 Nonstandard Problems.

5. Mathematics of Finance.
5.1 Simple and Compound Interest.
5.2 Future Value of an Annuity.
5.3 Present Value of an Annuity; Amortization.

6. Logic.
6.1 Statements and Quantifiers.
6.2 Truth Tables and Equivalent Statements.
6.3 The Conditional and Circuits.
6.4 More on the Conditional.
6.5 AnalyzingArguments with Euler Diagrams.
6.6 Analyzing Arguments with Truth Tables.

7. Sets and Probability.
7.1 Sets.
7.2 Applications of Venn Diagrams.
7.3 Introduction to Probability.
7.4 Basic Concepts of Probability.
7.5 Conditional Probability; Independent Events.
7.6 Bayes' Theorem.

8. Counting Principles; Further Probability Topics.
8.1 The Multiplication Principle; Permutations.
8.2 Combinations.
8.3 Probability Applications of Counting Principles.
8.4 Binomial Probability.
8.5 Probability Distributions; Expected Value.

9. Statistics.
9.1 Frequency Distributions; Measures of Central Tendency.
9.2 Measures of Variation.
9.3 The Normal Distribution.
9.4 Normal Approximation to the Binomial Distribution.

10. Nonlinear Functions.
10.1 Properties of Functions.
10.2 Quadratic Functions; Translation and Reflection.
10.3 Polynomial and Rational Functions.
10.4 Exponential Functions.
10.5 Logarithmic Functions.
10.6 Applications: Growth and Decay; Mathematics of Finance.

11. The Derivative.
11.1 Limits.
11.2 Continuity.
11.3 Rates of Change.
11.4 Definition of the Derivative.
11.5 Graphical Differentiation.

12. Calculating the Derivative.
12.1 Techniques for Finding Derivatives.
12.2 Derivatives of Products and Quotients.
12.3 The Chain Rule.
12.4 Derivatives of Exponential Functions.
12.5 Derivatives of Logarithmic Functions.

13. Graphs and the Derivative.
13.1 Increasing and Decreasing Functions.
13.2 Relative Extrema.
13.3 Higher Derivatives, Concavity, and the Second Derivative Test.
13.4 Curve Sketching.

14. Applications of the Derivative.
14.1 Absolute Extrema.
14.2 Applications of Extrema.
14.3 Further Business Applications: Economic Lot Size, Economic Order Quantity; Elasticity of Demand.
14.4 Implicit Differentiation.
14.5 Related Rates.
14.6 Differentials: Linear Approximation.

15. Integration.
15.1 Antiderivatives.
15.2 Substitution.
15.3 Area and the Definite Integral.
15.4 The Fundamental Theorem of Calculus.
15.5 The Area Between Two Curves.
15.6 Numerical Integration.

16. Further Techniques and Applications of Integration.
16.1 Integration by Parts.
16.2 Volume and Average Value.
16.3 Continuous Money Flow.
16.4 Improper Integrals.
16.5 Solutions of Elementary and Separable Differential Equations.

17. Multivariable Calculus.
17.1 Functions of Several Variables.
17.2 Partial Derivatives.
17.3 Maxima and Minima.
17.4 Lagrange Multipliers.
17.5 Total Differentials and Approximations.
17.6 Double Integrals.

18. Probability and Calculus.
18.1 Continuous Probability Models.
18.2 Expected Value and Variance of Continuous Random Variables.
18.3 Special Probability Density Functions.

Table 1: Formulas from Geometry.
Table 2: Area Under a Normal Curve.
Table 3: Integrals.

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