About this text
 How this text fits into the curriculum
 The Technology Used in this Text
 The Structure of the Book
 Homework Problems
 Reading Complex Texts
 Entering Student Profile
 Exiting Student Profile
  Mechanics and Techniques
  Application and Reasoning
  Communication and Professionalism
 Some Words About Level of Difficulty
 Some Words About Plagiarism and Working Together
 Copyright Notice
 Chapter Details
 Dedication and Acknowledgements
Contents
I  Quantifying the World
 Thinking of the world as data
 Key Thinking Strategy: Thinking of the world as data.
1 Problem Solving By Asking Questions
 1.1 Why Data?
  1.1.1 Definitions and Formulas
  1.1.2 Worked Examples
  1.1.3 Exploration 1A: Assumptions get in the way
 1.2 Defining the Problem
  1.2.1 Definitions and Formulas
  1.2.2 Worked Examples
  1.2.3 Exploration 1B: Beef N’ Buns Service
 1.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 1.4 Memo Problem: Carnivorous Cruise Lines
2 The Role of Data
 2.1 Extracting Data from the Problem Situation
  2.1.1 Definitions and Formulas
  2.1.2 Worked Examples
  2.1.3 Exploration 2A: Extracting Data at Beef n’ Buns
 2.2 Organizing data for Future Analysis
  2.2.1 Definitions and Formulas
  2.2.2 Worked Examples
  2.2.3 Exploration 2B: Entering Beef n’ Buns Data into a Spreadsheet
 2.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 2.4 Memo Problem: Carnivorous Cruise Lines, Part 2
3 Using Models to Interpret Data
 3.1 The Mean As A Model
  3.1.1 Definitions and Formulas
  3.1.2 Worked Examples
  3.1.3 Exploration 3A: Wait Times at Beef n’ Buns
 3.2 Categorical Data and Means
  3.2.1 Definitions and Formulas
  3.2.2 Worked Examples
  3.2.3 Exploration 3B: Gender Discrimination Analysis with Pivot Tables
 3.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 3.4 Memo Problem: Carnivorous Cruise Lines, Part 3
II  Analyzing Data Through Spatial Models
 Key Thinking Strategy: Asking Questions
4 Box Plots
 4.1 What Does ”Typical” Mean?
  4.1.1 Definitions and Formulas
  4.1.2 Worked Examples
  4.1.3 Exploration 4A: Koduck Salary Increases
 4.2 Thinking inside the box
  4.2.1 Definitions and Formulas
  4.2.2 Worked Examples
  4.2.3 Exploration 4B: Relationships Among Data, Statistics, and Boxplots
 4.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 4.4 Memo Problem: Matching Managers to a Company
  Follow-up Memo Problem
5 Histograms
 5.1 Getting the Data to Fit a Common Ruler
  5.1.1 Definitions and Formulas
  5.1.2 Worked Examples
  5.1.3 Exploration 5A: Cool Toys for Tots
 5.2 Profiling Your Data
  5.2.1 Definitions and Formulas
  5.2.2 Worked Examples
  5.2.3 Exploration 5B: Beef n’ Buns Service Times
 5.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 5.4 Memo Problem: Service at Beef n’ Buns
6 Interpreting Spatial Models
 6.1 Estimating Stats from Frequency Data
  6.1.1 Definitions and Formulas
  6.1.2 Worked Examples
  6.1.3 Exploration 6A: Data Summaries and Sensitivity
 6.2 Two Perspectives are Better than One
  6.2.1 Definitions and Formulas
  6.2.2 Worked Examples
  6.2.3 Exploration 6B: Stock Investment Decisions
 6.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 6.4 Memo Problem: Portfolio Analysis
III  Analyzing Data Through Linear Models
7 Correlation
 7.1 Picturing Two Variable Relationships
  7.1.1 Definitions and Formulas
  7.1.2 Worked Examples
  7.1.3 Exploration 7A: Predicting the Price of a Home
 7.2 Fitting a Line to Data
  7.2.1 Definitions and Formulas
  7.2.2 Worked Examples
  7.2.3 Exploration 7B: Adding Trendlines
 7.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 7.4 Memo Problem: Truck Maintenance Analysis
8 Simple Regression
 8.1 Modeling with Proportional Reasoning in Two Dimensions
  8.1.1 Definitions and Formulas
  8.1.2 Worked Examples
  8.1.3 Exploration 8A: Regression Modeling Practice
 8.2 Using and Comparing the Usefulness of a Proportional Model
  8.2.1 Definitions and Formulas
  8.2.2 Worked Examples
  8.2.3 Exploration 8B: How Outliers Influence Regression
 8.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 8.4 Memo Problem: Commuter Rail Analysis
9 Multiple Regression Models
 9.1 Modeling with Proportional Reasoning in Many Dimensions
  9.1.1 Definitions and Formulas
  9.1.2 Worked Examples
  9.1.3 Exploration 9A: Production Line Data
 9.2 Modeling with Qualitative Variables
  9.2.1 Definitions and Formulas
  9.2.2 Worked Examples
  9.2.3 Exploration 9B: Maintenance Cost for Trucks
 9.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 9.4 Memo Problem: Gender Discrimination
10 Is the Model Any Good
 10.1 Which coefficients are trustworthy?
  10.1.1 Definitions and Formulas
  10.1.2 Worked Examples
  10.1.3 Exploration 10A: Building a Trustworthy Model at EnPact
 10.2 More Complexity with Interaction Terms
  10.2.1 Definitions and Formulas
  10.2.2 Worked Examples
  10.2.3 Exploration 10B: Complex Gender Interactions at EnPact
 10.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 10.4 Memo Problem: Truck Maintenance Expenses, Part 2
IV  Analyzing Data with Nonlinear Models
11 Nonlinear Models Through Graphs
 11.1 What if the Data is Not Proportional
  11.1.1 Definitions and Formulas
  11.1.2 Worked Examples
  11.1.3 Exploration 11A: Non-proportional data
 11.2 Transformations of Graphs
  11.2.1 Definitions and Formulas
  11.2.2 Worked Examples
  11.2.3 Exploration 11B: Shifting and Scaling the Basic Models
 11.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 11.4 Memo Problem: DataCon Contract
12 Modeling with Nonlinear Data
 12.1 Non-proportional Regression Models
  12.1.1 Definitions and Formulas
  12.1.2 Worked Examples
  12.1.3 Exploration 12A: Learning and Production at Presario
 12.2 Interpreting a Non-proportional Model
  12.2.1 Definitions and Formulas
  12.2.2 Worked Examples
  12.2.3 Exploration 12B: What it means to be linear
 12.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 12.4 Memo Problem: Insurance Costs
13 Multivariate Nonlinear Models
 13.1 Models with Numerical Interaction Terms
  13.1.1 Definitions and Formulas
  13.1.2 Worked Examples
  13.1.3 Exploration 13A: Revenue and Demand Functions
 13.2 Interpreting Quadratic Models in Several Variables
  13.2.1 Definitions and Formulas
  13.2.2 Worked Examples
  13.2.3 Exploration 13B: Exploring Quadratic Models
 13.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 13.4 Memo Problem: Revenue Projections
V  Analyzing Data Using Calculus Models
14 Optimization
 14.1 Calculus with Powers and Polynomials
  14.1.1 Definitions and Formulas
  14.1.2 Worked Examples
  14.1.3 Exploration 14A: Finding the Derivative of a General Power Function
 14.2 Extreme Calculus!
  14.2.1 Definitions and Formulas
  14.2.2 Worked Examples
  14.2.3 Exploration 14B: Simple Regression Formulas
 14.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 14.4 Memo Problem: Profit Analysis
15 Logarithmic and Exponential Models
 15.1 Logarithms and their derivatives
  15.1.1 Definitions and Formulas
  15.1.2 Worked Examples
  15.1.3 Exploration 15A: Logs and distributions of data
 15.2 Compound interest and derivatives of exponentials
  15.2.1 Definitions and Formulas
  15.2.2 Worked Examples
  15.2.3 Exploration 15B: Loan Amortization
 15.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 15.4 Memo Problem: Loan Analysis
16 Optimization in Several Variables
 16.1 Constraints on Optimization
  16.1.1 Definitions and Formulas
  16.1.2 Worked Examples
  16.1.3 Exploration 16A: Setting up Optimization Problems
 16.2 Using Solver Table
  16.2.1 Definitions and Formulas
  16.2.2 Worked Examples
  16.2.3 Exploration 16B: Sensitivity Analysis
 16.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 16.4 Memo Problem: Advertising Costs
17 Area Under a Curve
 17.1 Calculating the Area under a Curve
  17.1.1 Definitions and Formulas
  17.1.2 Worked Examples
  17.1.3 Exploration 17A: Numerical Integration
 17.2 Applications of the Definite Integral
  17.2.1 Definitions and Formulas
  17.2.2 Worked Examples
  17.2.3 Exploration 17B: Consumers’ and Producers’ Surplus at Market Equilibrium
 17.3 Homework
  Mechanics and Techniques Problems
  Application and Reasoning Problems
 17.4 Memo Problem: Pricing Dispute
VI  Appendices
A Professional Writing
B Sample Rubric for Evaluating Memo 7