Interactive Finite Mathematics, 1st edition

Published by Pearson (February 26, 2021) © 2022

  • Nathan P. Ritchey Edinboro University of PA , Youngstown State University
  • Brian Rickard University of Arkansas
  • Roneet Merkin Florida International University

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For courses in Finite Mathematics.

Students learn math by seeing and doing 

Interactive Finite Mathematics engages finite math students through video. To foster deeper understanding, it weaves together short, dynamic videos, occasional text screens with key ideas and formulas, and MyLab Math assessment questions. It is built entirely in MyLab Math, replacing the traditional textbook with an online learning experience and using content that has undergone the same thoughtful development process as Pearson print textbooks. The flexibility of MyLab plus the authors' extensive teaching experience make this an ideal solution for traditional lecture, online, hybrid or flipped course formats.

Hallmark features of this title

  • A “watch a little, do a little” learning experience helps students master concepts. Interactive Assignments deliver video, assessment and occasional text-only screens to summarize key ideas. 
  • Short, dynamic videos deliver concepts so students can learn at their own pace. 
  • Visual and auditory cues, interactive figures, animations and other learning aids provided
  • Authored and narrated by mathematicians who are active in the classroom.
  • Extensive learning and teaching resources ease implementation and encourage active learning in any course format.
  • Integrated Review contains pre-made, assignable quizzes to assess the prerequisite skills needed for each chapter, plus personalized remediation for any gaps in skills that are identified.

1. Linear Functions

  • 1-1 Slopes and Equations of Lines
  • 1-2 Linear Functions and Applications
  • 1-3 The Least Squares Line
  • Chapter Review
  • Extended Application: Using Extrapolation to Predict Life Expectancy

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
  • Chapter Review
  • Extended Application: Contagion

3. Linear Programming: The Graphical Method

  • 3-1 Graphing Linear Inequalities
  • 3-2 Solving Linear Programming Problems Graphically
  • 3-3 Applications of Linear Programming
  • Chapter Review

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
  • Chapter Review
  • Extended Application: Using Integer Programming in the Stock-Cutting Problem

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
  • Chapter Review
  • Extended Application: Time, Money, and Polynomials

6. Logic

  • 6-1 Statements
  • 6-2 Truth Tables and Equivalent Statements
  • 6-3 The Conditional and Circuits
  • 6-4 More on the Conditional
  • 6-5 Analyzing Arguments and Proofs
  • 6-6 Analyzing Arguments with Quantifiers
  • Chapter Review
  • Extended Application: Logic Puzzles

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
  • Chapter Review
  • Extended Application: Medical Diagnosis

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
  • Chapter Review
  • Extended Application: Optimal Inventory for a Service Truck

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
  • Chapter Review
  • Extended Application: Statistics in the Law - The Castaneda Decision

10. Markov Chains

  • 10-1 Basic Properties of Markov Chains
  • 10-2 Regular Markov Chains
  • 10-3 Absorbing Markov Chains
  • Chapter Review
  • Extended Application: A Markov Chain Model for Teacher Retention

11. Game Theory

  • 11.1 Strictly Determined Games
  • 11.2 Mixed Strategies
  • 11.3 Game Theory and Linear Programming
  • Chapter Review
  • Extended Application: The Prisoner's Dilemma - Non-Zero-Sum Games in Economics

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
    Area Under a Normal Curve
    Answers to Selected Exercises
    Photo Acknowledgements
    Index

About our authors

Nathan P. Ritchey earned a B.A. in Mathematics with a minor in Music from Mansfield University of Pennsylvania. He earned an 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 a professor in the Department of Mathematics at Kent State 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.

Brian Rickard earned a B.S. in Mathematics, ME.d. in Higher Education, and a Ph.D. in Educational Statistics and Research Methods at the University of Arkansas. He joined the faculty of the J. William Fulbright College of Arts and Sciences at the University of Arkansas in 2009 where he is currently a Teaching Assistant Professor in the Department of Mathematical Sciences. In 2013 he was chosen to coordinate and overhaul the Finite Mathematics course into a flipped course and later an online course. He has created over 170 mathematics videos currently in use in Pearson products and conducts research in competing risks analysis, retention and graduation, and university tutoring centers.

Roneet Merkin earned a B.A. in Mathematics from Barnard College and a Master's degree in Mathematics from City College of New York. She joined the faculty at Florida International University in 2014, where she is currently an Instructor in the Department of Mathematics and Statistics as well as Program Director for the Mastery Math Lab. In 2015 she redesigned FIU's online Finite Math course, and in 2016 she co-designed their hybrid Finite Math course. Additionally, Roneet has helped transform several of FIU's 1000-level courses into inquiry-based, active learning courses. She has written over 100 conceptual questions currently in use in the Pearson Finite MyLab Math course by Lial/Greenwell/Ritchey. Roneet's passion is not just teaching math but making math more teachable.

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