MyLab Statistics for Interactive Statistics: Informed Decisions Using Data eCourse -- Access Card -- PLUS Guided Notebook / Edition 2

by Michael Sullivan III, George Woodbury

Overview

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013522926X / 9780135229262 MyLab Statistics for Interactive Statistics: Informed Decisions Using Data eCourse — Access Card — PLUS Guided Notebook, 2/e

Package consists of:

0134673522 / 9780134673523 Interactive Statistics: Informed Decisions Using Data Student Access Kit, 2/e

013472240X / 9780134722405 Student Guided Notebook for Interactive Statistics: Informed Decisions Using Data, 2/e

Product Details

ISBN-13:	9780135229262
Publisher:	Pearson Education
Publication date:	03/22/2018
Edition description:	2nd ed.
Pages:	9998
Product dimensions:	8.30(w) x 10.70(h) x 0.80(d)

About the Author

Mike Sullivan, III, has training in mathematics, statistics, and economics, and brings a varied teaching background that includes 15 years of instruction in both high school and college-level. He is currently a full-time professor of mathematics and statistics at Joliet Junior College. Mike has numerous textbooks in publication, in addition to his Introductory Statistics Series, which include series in both Developmental Mathematics and Precalculus (written with his father, Michael Sullivan). Mike has built this new statistics book in the classroom using feedback from his students. He is well aware of the challenges faced by students taking an introductory statistics course. Mike’s goal is for students to be more informed interpreters of data so that they will be better decision makers and have stronger critical-thinking skills. When not in the classroom or writing, Michael enjoys spending time with his three children, Michael, Kevin, and Marissa, and playing golf.

George Woodbury earned a bachelor’s degree in Mathematics from the University of California—Santa Barbara and a master’s degree in Mathematics from California State University—Northridge. He currently teaches at College of the Sequoias in Visalia, CA, just outside of Fresno. George has been honored as an instructor by both his students and his colleagues. Aside from teaching and writing, George served as the department chair of the math/engineering division from 1999 through 2004.

Table of Contents

1. Data Collection
   • 1.1 Introduction to the Practice of Statistics
   • 1.2 Observational Studies versus Designed Experiments
   • 1.3 Simple Random Sampling
   • 1.4 Other Effective Sampling Methods
   • 1.5 Bias in Sampling
   • 1.6 The Design of Experiments
   • Chapter Review
   • Chapter Test
   • Making an Informed Decision: What College Should I Attend?
   • Case Study: Chrysalises for Cash

1. Organizing and Summarizing Data
   • 2.1 Organizing Qualitative Data
   • 2.2 Organizing Quantitative Data: The Popular Displays
   • 2.3 Additional Displays of Quantitative Data
   • 2.4 Graphical Misrepresentations of Data
   • Chapter Review
   • Chapter Test
   • Making an Informed Decision: Tables or Graphs?
   • Case Study: The Day the Sky Roared
2. Numerically Summarizing Data
   • 3.1 Measures of Central Tendency
   • 3.2 Measures of Dispersion
   • 3.3 Measures of Central Tendency and Dispersion from Grouped Data
   • 3.4 Measures of Position
   • 3.5 The Five-Number Summary and Boxplots
   • Chapter Review
   • Chapter Test
   • Making an Informed Decision: What Car Should I Buy?
   • Case Study: Who Was “A Mourner”?
3. Describing the Relation Between Two Variables
   • 4.1 Scatter Diagrams and Correlation
   • 4.2 Least-Squares Regression
   • 4.3 Diagnostics on the Least-Squares Regression Line
   • 4.4 Contingency Tables and Association
   • Chapter Review
   • Chapter Test
   • Making an Informed Decision: Relationships Among Variables on a World Scale
   • Case Study: Thomas Malthus, Population, and Subsistence

1. Probability
   • 5.1 Probability Rules
   • 5.2 The Addition Rule and Complements
   • 5.3 Independence and the Multiplication Rule
   • 5.4 Conditional Probability and the General Multiplication Rule
   • 5.5 Counting Techniques
   • 5.6 Simulation
   • 5.7 Putting It Together: Which Method Do I Use?
   • Chapter Review
   • Chapter Test
   • Making an Informed Decision: What Are the Effects of Drinking and Driving?
   • Case Study: The Case of the Body in the Bag
2. Discrete Probability Distributions
   • 6.1 Discrete Random Variables
   • 6.2 The Binomial Probability Distribution
   • 6.3 The Poisson Probability Distribution
   • Chapter Review
   • Chapter Test
   • Making an Informed Decision: Should We Convict?
   • Case Study: The Voyage of the St. Andrew
3. The Normal Probability Distribution
   • 7.1 Properties of the Normal Distribution
   • 7.2 Applications of the Normal Distribution
   • 7.3 Assessing Normality
   • 7.4 The Normal Approximation to the Binomial Probability Distribution
   • Chapter Review
   • Chapter Test
   • Making an Informed Decision: What Stock Do I Pick?
   • Case Study: A Tale of Blood, Chemistry, and Health

1. Sampling Distributions
   • 8.1 Distribution of the Sample Mean
   • 8.2 Distribution of the Sample Proportion
   • Chapter Review
   • Chapter Test
   • Making an Informed Decision: How Would You Break Down Your Day?
   • Case Study: Sampling Distribution of the Median
2. Estimating the Value of a Parameter Using Confidence Intervals
   • 9.1 Estimating a Population Proportion
   • 9.2 Estimating a Population Mean
   • 9.3 Putting It Together: Which Procedure Do I Use?
   • 9.4 Estimating with Bootstrapping
   • Chapter Review
   • Chapter Test
   • Making an Informed Decision: How Much Should I Spend for this House?
   • Case Study: When Model Requirements Fail
3. Hypothesis Tests Regarding a Parameter
   • 10.1 The Language of Hypothesis Testing
   • 10.2A Hypothesis Tests on a Population Proportion with Simulation
   • 10.2B Hypothesis Tests on a Population Proportion Using the Normal Model
   • 10.3A Using Simulation/Bootstrapping in Hypothesis Tests for a Population Mean
   • 10.3B Hypothesis Tests for a Population Mean
   • 10.4 Putting It Together: Which Procedure Do I Use?
   • Chapter Review
   • Chapter Test
   • Making an Informed Decision: Selecting a Mutual Fund
   • Case Study: How Old Is Stonehenge?
4. Inference on Two Samples
   • 11.1A Using Randomization Techniques to Compare Two Proportions
   • 11.1 Inference about Two Population Proportions: Independent Samples
   • 11.2A Using Bootstrapping to Conduct Inference on Two Dependent Means
   • 11.2 Inference about Two Population Means: Dependent Samples
   • 11.3A Using Randomization Techniques to Compare Two Independent Means
   • 11.3 Inference about Two Population Means: Independent Samples
   • 11.4 Putting It Together: Which Procedure Do I Use?
   • Chapter Review
   • Chapter Test
   • Making an Informed Decision: Which Car Should I Buy?
   • Case Study: Control in the Design of Experiment
5. Inference on Categorical Data
   • 12.1 Goodness-of-Fit Test
   • 12.2 Tests for Independence and the Homogeneity of Proportions
   • 12.3 Inference about Two Population Proportions: Dependent Samples
   • Chapter Review
   • Chapter Test
   • Making an Informed Decision: What Are the Benefits of College?
   • Case Study: Feeling Lucky? Well, Are You?
6. Comparing Three or More Means
   • 13.1 Comparing Three or More Means: One-Way Analysis of Variance
   • 13.2 Post-Hoc Tests on One-Way Analysis of Variance
   • Chapter Review
   • Chapter Test
   • Making an Informed Decision: Where Should I Invest?
   • Case Study: Hat Size and Intelligence
7. Inference of the Least-Squares Regression Model
   • 14.1A Using Randomization Techniques on the Slope of the Least-Squares Regression Line
   • 14.1 Testing the Significance of the Least-Squares Regression Model
   • 14.2 Confidence and Prediction Intervals
   • Chapter Review
   • Chapter Test
   • Making an Informed Decision: Buying a Home
   • Case Study: Housing Boom

• C.1 The Normal Approximation to the Binomial Probability Distribution
• C.2 Estimating a Population Standard Deviation
• C.3 Hypothesis Tests for a Population Standard Deviation