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Cover type: Hardback

Edition: 07

Copyright: 2007

Publisher: Houghton Mifflin Harcourt

Published: 2007

International: No

Edition: 07

Copyright: 2007

Publisher: Houghton Mifflin Harcourt

Published: 2007

International: No

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Geared toward business and social science majors in a two-semester finite mathematics and applied calculus course, this text equips students with the analytical tools and technological skills they will need in the workplace. Plain language and an easy-to-read style help stress conceptual understanding and reinforce key terms and concepts. At the same time, the incorporation of real-life applications, examples, and data help engage students--even those who have never enjoyed mathematics. Pedagogy throughout the text helps students analyze data from a variety of approaches, including numeric, algebraic, graphical, literal, and technological. A robust supplement package and exciting new technology program provide students with extensive learning and support, so that instructors can spend more time teaching.

- Make It Real projects ask students to collect and analyze data that often mirrors their own experiences. Students are able to better process this information and connect math to their own lives.
- Technology Tips are scattered throughout the text and help guide students through new techniques on the graphing calculator such as graphing a function, solving an equation, or finding the value of a function.
- Examples, Exercises, and Applications focus on the business or social science student and are based on engaging real-life data.
- Eduspace, powered by Blackboard, Houghton Mifflin's online learning tool brings your students quality online homework, tutorials, multimedia, and testing that correspond to the Finite Mathematics and Applied Calculus text. This content is paired with the recognized course management tools of Blackboard. Use Eduspace to teach all or part of a course online.
- Streamlined content allows instructors to cover the text in its entirety.

Chapter 1

Functions

Linear Functions

Linear Models

Chapter 2

Systems of Two-Variable Linear Equations

Using Matrices to Solve Linear Systems of Equations

Linear System Applications

Chapter 3

Matrix Addition and Scalar Multiplication

Matrix Multiplication and Inverses

Solving Matrix Equations

Leontief Input-Output Models

Chapter 4

Graphing Linear Inequalities

Graphically Solving Linear Programming Problems

The Simplex Method: Solving Standard Maximization Problems

Standard Minimization Problems and the Dual

The Simplex Method: Solving Problems with Mixed Constraints

Chapter 5

Quadratic Function Models

Higher Order Polynomial Function Models

Exponential Models

Logarithmic Models

Choosing a Mathematical Model

Chapter 6

Solving Exponential and Logarithmic Equations

Simple Interest and Compound Interest

Future Value of an Increasing Annuity

Present Value of a Decreasing Annuity

Chapter 7

Sets

Cardinality and the Addition and Multiplication Principles

Permutations and Combinations

Introduction to Probability

Basic Probability Concepts

Chapter 8

Conditional Probability

Bayes' Theorem

Markov Chains

Random Variables and Expected Value

Measures of Central Tendency and Dispersion

Normal Distributions

Chapter 9

Average Rates of Change

Limits and Instantaneous Rates of Change

The Derivative as a Slope: Graphical Method

The Derivative as a Function: Algebraic Method

Interpreting the Derivative

Chapter 10

10.1 Basic Derivative Rules

10.2 Product Rule

10.3 Chain Rule

10.4 Exponential and Logarithmic Rules

10.5 Implicit Differentiation

Chapter 11

11.1 Maxima and Minima

11.2 Applications of Maxima and Minima

11.3 Concavity an the Second Derivative

11.4 Related Rates

Chapter 12

12.1 The Indefinite Integral

12.2 Integration by Substitution

Using Sums to Approximate Area

The Definite Integral

The Fundamental Theorem of Calculus

Chapter 13

Integration by Parts

Area Between Two Curves

The Differential Equations and Applications

The Differential Equations: Limited Growth and Logistic Models

Chapter 14

Multivariable Functions

Partial Derivatives

Multivariable Maxima and Minima

14.4 Constrained Maxima and Minima and Applications

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Summary

Geared toward business and social science majors in a two-semester finite mathematics and applied calculus course, this text equips students with the analytical tools and technological skills they will need in the workplace. Plain language and an easy-to-read style help stress conceptual understanding and reinforce key terms and concepts. At the same time, the incorporation of real-life applications, examples, and data help engage students--even those who have never enjoyed mathematics. Pedagogy throughout the text helps students analyze data from a variety of approaches, including numeric, algebraic, graphical, literal, and technological. A robust supplement package and exciting new technology program provide students with extensive learning and support, so that instructors can spend more time teaching.

- Make It Real projects ask students to collect and analyze data that often mirrors their own experiences. Students are able to better process this information and connect math to their own lives.
- Technology Tips are scattered throughout the text and help guide students through new techniques on the graphing calculator such as graphing a function, solving an equation, or finding the value of a function.
- Examples, Exercises, and Applications focus on the business or social science student and are based on engaging real-life data.
- Eduspace, powered by Blackboard, Houghton Mifflin's online learning tool brings your students quality online homework, tutorials, multimedia, and testing that correspond to the Finite Mathematics and Applied Calculus text. This content is paired with the recognized course management tools of Blackboard. Use Eduspace to teach all or part of a course online.
- Streamlined content allows instructors to cover the text in its entirety.

Table of Contents

Chapter 1

Functions

Linear Functions

Linear Models

Chapter 2

Systems of Two-Variable Linear Equations

Using Matrices to Solve Linear Systems of Equations

Linear System Applications

Chapter 3

Matrix Addition and Scalar Multiplication

Matrix Multiplication and Inverses

Solving Matrix Equations

Leontief Input-Output Models

Chapter 4

Graphing Linear Inequalities

Graphically Solving Linear Programming Problems

The Simplex Method: Solving Standard Maximization Problems

Standard Minimization Problems and the Dual

The Simplex Method: Solving Problems with Mixed Constraints

Chapter 5

Quadratic Function Models

Higher Order Polynomial Function Models

Exponential Models

Logarithmic Models

Choosing a Mathematical Model

Chapter 6

Solving Exponential and Logarithmic Equations

Simple Interest and Compound Interest

Future Value of an Increasing Annuity

Present Value of a Decreasing Annuity

Chapter 7

Sets

Cardinality and the Addition and Multiplication Principles

Permutations and Combinations

Introduction to Probability

Basic Probability Concepts

Chapter 8

Conditional Probability

Bayes' Theorem

Markov Chains

Random Variables and Expected Value

Measures of Central Tendency and Dispersion

Normal Distributions

Chapter 9

Average Rates of Change

Limits and Instantaneous Rates of Change

The Derivative as a Slope: Graphical Method

The Derivative as a Function: Algebraic Method

Interpreting the Derivative

Chapter 10

10.1 Basic Derivative Rules

10.2 Product Rule

10.3 Chain Rule

10.4 Exponential and Logarithmic Rules

10.5 Implicit Differentiation

Chapter 11

11.1 Maxima and Minima

11.2 Applications of Maxima and Minima

11.3 Concavity an the Second Derivative

11.4 Related Rates

Chapter 12

12.1 The Indefinite Integral

12.2 Integration by Substitution

Using Sums to Approximate Area

The Definite Integral

The Fundamental Theorem of Calculus

Chapter 13

Integration by Parts

Area Between Two Curves

The Differential Equations and Applications

The Differential Equations: Limited Growth and Logistic Models

Chapter 14

Multivariable Functions

Partial Derivatives

Multivariable Maxima and Minima

14.4 Constrained Maxima and Minima and Applications

Publisher Info

Publisher: Houghton Mifflin Harcourt

Published: 2007

International: No

Published: 2007

International: No

Geared toward business and social science majors in a two-semester finite mathematics and applied calculus course, this text equips students with the analytical tools and technological skills they will need in the workplace. Plain language and an easy-to-read style help stress conceptual understanding and reinforce key terms and concepts. At the same time, the incorporation of real-life applications, examples, and data help engage students--even those who have never enjoyed mathematics. Pedagogy throughout the text helps students analyze data from a variety of approaches, including numeric, algebraic, graphical, literal, and technological. A robust supplement package and exciting new technology program provide students with extensive learning and support, so that instructors can spend more time teaching.

- Make It Real projects ask students to collect and analyze data that often mirrors their own experiences. Students are able to better process this information and connect math to their own lives.
- Technology Tips are scattered throughout the text and help guide students through new techniques on the graphing calculator such as graphing a function, solving an equation, or finding the value of a function.
- Examples, Exercises, and Applications focus on the business or social science student and are based on engaging real-life data.
- Eduspace, powered by Blackboard, Houghton Mifflin's online learning tool brings your students quality online homework, tutorials, multimedia, and testing that correspond to the Finite Mathematics and Applied Calculus text. This content is paired with the recognized course management tools of Blackboard. Use Eduspace to teach all or part of a course online.
- Streamlined content allows instructors to cover the text in its entirety.

Chapter 1

Functions

Linear Functions

Linear Models

Chapter 2

Systems of Two-Variable Linear Equations

Using Matrices to Solve Linear Systems of Equations

Linear System Applications

Chapter 3

Matrix Addition and Scalar Multiplication

Matrix Multiplication and Inverses

Solving Matrix Equations

Leontief Input-Output Models

Chapter 4

Graphing Linear Inequalities

Graphically Solving Linear Programming Problems

The Simplex Method: Solving Standard Maximization Problems

Standard Minimization Problems and the Dual

The Simplex Method: Solving Problems with Mixed Constraints

Chapter 5

Quadratic Function Models

Higher Order Polynomial Function Models

Exponential Models

Logarithmic Models

Choosing a Mathematical Model

Chapter 6

Solving Exponential and Logarithmic Equations

Simple Interest and Compound Interest

Future Value of an Increasing Annuity

Present Value of a Decreasing Annuity

Chapter 7

Sets

Cardinality and the Addition and Multiplication Principles

Permutations and Combinations

Introduction to Probability

Basic Probability Concepts

Chapter 8

Conditional Probability

Bayes' Theorem

Markov Chains

Random Variables and Expected Value

Measures of Central Tendency and Dispersion

Normal Distributions

Chapter 9

Average Rates of Change

Limits and Instantaneous Rates of Change

The Derivative as a Slope: Graphical Method

The Derivative as a Function: Algebraic Method

Interpreting the Derivative

Chapter 10

10.1 Basic Derivative Rules

10.2 Product Rule

10.3 Chain Rule

10.4 Exponential and Logarithmic Rules

10.5 Implicit Differentiation

Chapter 11

11.1 Maxima and Minima

11.2 Applications of Maxima and Minima

11.3 Concavity an the Second Derivative

11.4 Related Rates

Chapter 12

12.1 The Indefinite Integral

12.2 Integration by Substitution

Using Sums to Approximate Area

The Definite Integral

The Fundamental Theorem of Calculus

Chapter 13

Integration by Parts

Area Between Two Curves

The Differential Equations and Applications

The Differential Equations: Limited Growth and Logistic Models

Chapter 14

Multivariable Functions

Partial Derivatives

Multivariable Maxima and Minima

14.4 Constrained Maxima and Minima and Applications