Math114Q - Quantitative Reasoning

Credits: 3

Course Description: This course covers the basic algebra and technological tools used in the social, physical and life sciences to analyze quantitative information. The emphasis is on real world, open-ended problems that involve reading, writing, calculating, synthesizing, and clearly reporting results. Topics include descriptive statistics, linear, and exponential models. Technology used in the course includes computers (spreadsheets, internet) and graphing calculators.

Pre-Requisites: Math placement test A.

Frequency:

Current Textbook:
Explorations in College Algebra, 4th Edition, by Linda Kime, Judy Clark, and Beverly Michael, published by John Wiley & Sons, 2008, ISBN 978-0-470-40954-1,
OR
Using and Understanding Mathematics: A Quantitative Reasoning Approach, 4th Edition, by Jeffrey O. Bennett and William L. Briggs, published by Addison-Wesley, 2008.
Check with your instructor to make sure this is the textbook used for your section.

Fall 2008 Schedule:

Section	Meeting Time	Instructor
1	MWF 8:00am-8:50am	Judith Burch
2	MWF 9:00am-9:50am	Judith Burch
3	MWF 10:00am-10:50am	Robert Rosenfeld
4	MWF 11:00am-11:50pm	Monique Fuguet
5	MWF 12:00pm-12:50pm	Mark Pawlak
6	MWF 1:00pm-1:50pm	Mitchell Silver
7	TuTh 8:00am-9:15am	Monique Fuguet
8	TuTh 9:30am-10:45am	Joseph Sheppeck
9	TuTh 11:00am-12:15pm	Maura Mast
10	TuTh 12:30pm-1:45pm	Jeremiah Russell
11	TuTh 2:00pm-3:15pm	Ethan Bolker

Topics

Chapter 1: 1.1 An Introduction to Single Variable Data
1.2 Writing about Data
1.3 Visualizing two Variable Data
1.4 Interpreting Equations and Their Graphs
1.5 An Introduction to Functions
1.6 The Language of Functions
Exploration 1.1: Collecting, Representing, and Analyzing Data
Chapter 2: 2.1 Average Rates of Changes
2.2 Change in the Average Rate of Change
2.3 The Average Rate of Change in a Slope
2.4 Putting a Slant on Data
2.5 When Rates of Change are Constant
2.6 Linear Functions
2.7 Special Cases
2.8 Finding Linear Models for Data
Exploration 2.1: Having it your Way
    Using US Census Data
    Summarizing the Data: Regression Lines
    Interpreting Regression Lines: Correlation vs. Causation
    Next Steps: Raising More questions
Chapter 4: 4.1 Measuring Time and Space: The Numbers of Science
4.2 Simplifying Expressions with Positive Integer Exponents
4.3 Simplifying Expressions with Negative Integer Exponents
4.4 Converting Units
4.5 Simplifying Expressions with Fractional Exponents
4.6 Orders of Magnitude
Chapter 5: 5.1 Exponential Growth
5.2 Exponential Decay
5.3 The Graphs of Exponential Functions
5.4 Exponential Growth or Decay Expressed in Percentages
5.5 Examples of Exponential Growth and Decay
5.6 Semi-Log Plots of Exponential Functions
Exploration 5.2: Recognizing Exponential Patterns in Data Tables

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Page last modified: September 2, 2008			Department of Mathematics University of Massachusetts Boston Phone: 617-287-6460; Fax: 617-287-6433 Information: Webmaster: