Mathematics for Life
A Foundation Course for Quantitative Literacy (Preliminary Edition)
Published on 29. July 1998
Book
Paperback/Softback
552 pages
978-0-13-493859-2 (ISBN)
Description
For computer-based courses in Quantitative Literacy or Liberal Arts Mathematics.
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.
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.
More details
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
Professional and scholarly
Dimensions
Height: 278 mm
Width: 216 mm
Thickness: 21 mm
Weight
1183 gr
ISBN-13
978-0-13-493859-2 (9780134938592)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Content
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.
ACTIVITIES.
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.
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.
ACTIVITIES.
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.