[Book Cover]

Mathematics for Life: A Foundation Course for Quantitative Literacy (Preliminary Edition), 1/e

Donald Pierce, Western Oregon State University
Edward B. Wright, Western Oregon State University

Published January, 1997 by Prentice Hall Engineering/Science/Mathematics

Copyright 1997, 552 pp.
ISBN 0-13-493859-3

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Designed to teach students to use mathematics and technologies in formulating and solving real-world problems. This lab-based text focuses on developing quantitative reasoning skills and requires students to work collaboratively in small groups. Combining technology with cooperative learning strategies creates a rich experiential learning environment where instructors become facilitators rather than lecturers, and students learn skills that can improve their performance in subsequent courses and later in life.


Develops proficiencies in both mathematics and computer science.
Implements National Guidelines for Content and Pedagogy as recommended by NCTM, MAA/AMS, AAAS, And NRC.
Features an activity-based approach that focuses on cooperative and discovery learning.
Focuses on applied critical thinking throughout.
Offers individual, group, and self-assessment opportunities.
Emphasizes computer skill development.
Explores the true integration of technology — requires the use of word processors and spreadsheets.
Uses current real-world data from the Internet concerning real issues.
Fully integrates writing — through the use of daily journals, reports and projects.
The text format permits the easy development of additional topics by the instructor.

Table of Contents

    1. Literacy.

      The Economic Value of Literacy. The Social value of Literacy. Identifying and Developing Necessary Skills. Course Mechanics. Group Dynamics.

    2. Computers and Operating Systems.

      A Brief History of Computers. Computing and Operating Systems.

    3. Learning and Working in Groups.

      What is learning, and how do we measure it? The Components of Knowledge. Levels of Learning. How We Learn. Natural Abilities. Thinking Skills. Learning in Teams. Roles Within Teams. Team Strategies.

    4. Mathematics —A Historical Perspective.

      The roots of civilization. Numeral Systems. Basic Operations. Arithmetic. Modern Numeral Systems.

    5. Algebra and Spreadsheets.

      Egyptian Algebra. Babylonian Algebra. Greek Algebra. Indian Algebra. The Language of Algebra. Spreadsheets—Getting Started. Connecting Algebra to Spreadsheets.

    6. Statistics.

      A Brief History of Statistics. Statistics Today. Descriptive Statistics. Statistics—Uses and Abuses.

    7. Apportionment.

      A Brief History of apportionment. Basic Terminology. Methods of Apportionment.

    8. Functions and Modeling.

      Basic Units of Measurement. Modeling the Heavens. Linear Models. Exponential Models. Relations and Functions. Curve Fitting. The Method of Least Sqaures. Case Studies.

    9. Probability and Inferential Statistics.

      Epirical Probalbility. Games of Chance. The Binomial Distribution. The Normal Distribution. Sampling Distribution of a Statistic. Satistical inference. Hypothesis Testing. Small Samples.

    10. Internet Essentials.

      A Brief History of the Internet. Electronic Mail. Finding Information on the Web. Surfing Cyberspace. Internet Glossary.
    Introduction to DOS and Windows.
    First Group Process Day.
    Word Processing.
    Accessing Information Electronically #1.
    Basics of Spreadsheets.
    Descriptive Statistics on the Spreadsheet, I.
    Descriptive Statistics on the Spreadsheet, II.
    Descriptive Statistics on the Spreadsheet, III.
    Spreadsheet Application Apportionment.
    Second Group Process Day.
    Variables aRelations and Functions.
    Linear Functions.
    Exponential Functions.
    Power and Inverse Functions.
    Modeling Growth and Change.
    Curve Fitting, I.
    Curve Fitting, II — Equations of Best Fit 1.
    Curve Fitting, III — Equations of Best Fit 2.
    Third Group Process Day.
    Curve Fitting, IV — Prediction.
    Report Writing.
    Introduction to Probability.
    Binomial and Normal Distributions.
    Distribution of the Sample Mean.
    Confidence Intervals.
    Hypothesis Testing, I — Large Samples.
    Hypothesis Testing, II — Small Samples.


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