Skip to main content

Humanities, Social Science and Language


Digital Products


Connect®
Course managementreporting, and student learning tools backed by great support.

McGraw Hill GO
Greenlight learning with the new eBook+

ALEKS®
Personalize learning and assessment

ALEKS® Placement, Preparation, and Learning
Achieve accurate math placement

SIMnet
Ignite mastery of MS Office and IT skills

McGraw Hill eBook & ReadAnywhere App
Get learning that fits anytime, anywhere

Sharpen: Study App
A reliable study app for students

Virtual Labs
Flexible, realistic science simulations

Services


Inclusive Access
Reduce costs and increase success

LMS Integration
Log in and sync up

Math Placement
Achieve accurate math placement

Content Collections powered by Create®
Curate and deliver your ideal content

Custom Courseware Solutions
Teach your course your way

Professional Services
Collaborate to optimize outcomes

Remote Proctoring
Validate online exams even offsite

Institutional Solutions
Increase engagement, lower costs, and improve access for your students

Support


General Help & Support Info
Customer Service & Tech Support contact information

Online Technical Support Center
FAQs, articles, chat, email or phone support

Support At Every Step
Instructor tools, training and resources for ALEKS, Connect & SIMnet

Instructor Sample Requests
Get step by step instructions for requesting an evaluation, exam, or desk copy

Platform System Check
System status in real time

Loose Leaf for Elementary Statistics with ALEKS 360 Access Card (18 weeks)
Loose Leaf for Elementary Statistics with ALEKS 360 Access Card (18 weeks)

Loose Leaf for Elementary Statistics with ALEKS 360 Access Card (18 weeks), 3rd Edition

ISBN10: 1260487547 | ISBN13: 9781260487541
By William Navidi and Barry Monk
© 2019

Format Options:

* The estimated amount of time this product will be on the market is based on a number of factors, including faculty input to instructional design and the prior revision cycle and updates to academic research-which typically results in a revision cycle ranging from every two to four years for this product. Pricing subject to change at any time.

Instructor Information

Quick Actions (Only for Validated Instructor Accounts):

Navidi/Monk, Elementary Statistics was developed around three central themes – Clarity, Quality, and Accuracy. These central themes were born out of extensive market research and feedback from statistics instructors across the country. The authors paid close attention to how material is presented to students, ensuring that the content in the text is very clear, concise, and digestible. High quality exercises, examples and integration of technology are important aspects of an Introductory Statistics text. The authors have provided robust exercise sets that range in difficulty. They have also focused keen attention to ensure that examples provide clear instruction to students. Technology is integrated throughout the text, providing students examples of how to use the TI-84 Plus Graphing Calculators, Microsoft Excel and Minitab. The accuracy of Elementary Statistics was a foundational principle always on the minds of the authors. While this certainly pertains to all aspects of the text, the authors also exhausted energy in ensuring the supplements have been developed to fit cohesively with the text.

Table of Contents—Elementary Statistics, Third Edition

Chapter 1: Basic Ideas

1.1 Sampling

1.2 Types of Data

1.3 Design of Experiments

1.4 Bias in Studies

Chapter 1 Summary

Chapter Quiz

Chapter 1 Review Exercises

Case Study

Chapter 2: Graphical Summaries of Data

2.1 Graphical Summaries for Qualitative Data

2.2 Frequency Distributions and Their Graphs

2.3 More Graphs for Quantitative Data

2.4 Graphs Can Be Misleading

Chapter 2 Summary

Chapter Quiz

Chapter 2 Review Exercises

Case Study

Chapter 3: Numerical Summaries of Data

3.1 Measures of Center

3.2 Measures of Spread

3.3 Measures of Position

Chapter 3 Summary

Chapter Quiz

Chapter 3 Review Exercises

Case Study

Chapter 4: Summarizing Bivariate Data

4.1 Correlation

4.2 The Least-Squares Regression Line

4.3 Features and Limitations of the Least-Squares Regression Line

Chapter 4 Summary

Chapter Quiz

Chapter 4 Review Exercises

Case Study

Chapter 5: Probability

5.1 Basic Concepts of Probability

5.2 The Addition Rule and the Rule of Complements

5.3 Conditional Probability and the Multiplication Rule

5.4 Counting

Chapter 5 Summary

Chapter Quiz

Chapter 5 Review Exercises

Case Study

Chapter 6: Discrete Probability Distributions

6.1 Random Variables

6.2 The Binomial Distribution

6.3 The Poisson Distribution

Chapter 6 Summary

Chapter Quiz

Chapter 6 Review Exercises

Case Study

Chapter 7: The Normal Distribution

7.1 The Standard Normal Curve

7.2 Applications of the Normal Distribution

7.3 Sampling Distributions and the Central Limit Theorem

7.4 The Central Limit Theorem for Proportions

7.5 The Normal Approximation to the Binomial Distribution

7.6 Assessing Normality

Chapter 7 Summary

Chapter Quiz

Chapter 7 Review Exercises

Case Study

Chapter 8: Confidence Intervals

8.1 Confidence Intervals for a Population Mean, Standard Deviation Known

8.2 Confidence Intervals for a Population Mean, Standard Deviation Unknown

8.3 Confidence Intervals for a Population Proportion

8.4 Confidence Intervals for a Standard Deviation

8.5 Determining Which Method to Use

Chapter 8 Summary

Chapter Quiz

Chapter 8 Review Exercises

Case Study

Chapter 9: Hypothesis Testing

9.1 Basic Principles of Hypothesis Testing

9.2 Hypothesis Tests for a Population Mean, Standard Deviation Known

9.3 Hypothesis Tests for a Population Mean, Standard Deviation Unknown

9.4 Hypothesis Tests for Proportions

9.5 Hypothesis Tests for a Standard Deviation

9.6 Determining Which Method to Use

9.7 Power

Chapter 9 Summary

Chapter Quiz

Chapter 9 Review Exercises

Case Study

Chapter 10: Two-Sample Confidence Intervals

10.1 Confidence Intervals for the Difference Between Two Means: Independent Samples

10.2 Confidence Intervals for the Difference Between Two Proportions

10.3 Confidence Intervals for the Difference Between Two Means: Paired Samples

Chapter 10 Summary

Chapter Quiz

Chapter 10 Review Exercises

Case Study

Chapter 11: Two-Sample Hypothesis Tests

11.1 Hypothesis Tests for the Difference Between Two Means: Independent Samples

11.2 Hypothesis Tests for the Difference Between Two Proportions

11.3 Hypothesis Tests for the Difference Between Two Means: Paired Samples

11.4 Hypothesis Tests for Two Population Standard Deviations

11.5 The Multiple Testing Problem

Chapter 11 Summary

Chapter Quiz

Chapter 11 Review Exercises

Case Study

Chapter 12: Tests with Qualitative Data

12.1 Testing Goodness of Fit

12.2 Tests for Independence and Homogeneity

Chapter 12 Summary

Chapter Quiz

Chapter 12 Review Exercises

Case Study

Chapter 13: Inference in Linear Models

13.1 Inference on the Slope of the Regression Line

13.2 Inference About the Response

13.3 Multiple Regression

Chapter 13 Summary

Chapter Quiz

Chapter 13 Review Exercises

Case Study

Chapter 14: Analysis of Variance

14.1 One-way Analysis of Variance

14.2 Two-way Analysis of Variance

Chapter 14 Summary

Chapter Quiz

Chapter 14 Review Exercises

Case Study

Chapter 15: Nonparametric Statistics

15.1 The Sign Test

15.2 The Rank-Sum Test

15.3 The Signed-Rank Test

Chapter 15 Summary

Chapter Quiz

Chapter 15 Review Exercises

Case Study

Appendix A: Tables


Appendix B: TI-84 PLUS Stat Wizards


About the Author

William Navidi

William Navidi received a B.A. in mathematics from New College, an M.A in mathematics from Michigan State University, and a Ph.D. in statistics from the University of California at Berkeley. Dr. Navidi is a professor of applied mathematics and statistics at the Colorado School of Mines in Golden, Colorado. He began his teaching career at the County College of Morris in Dover, New Jersey. He has taught mathematics and statistics at all levels, from developmental through the graduate level. Dr. Navidi has written two engineering statistics textbooks for McGraw-Hill and has authored more than 50 research papers, both in statistical theory and in a wide variety of applications, including computer networks, epidemiology, molecular biology, chemical engineering, and geophysics.

Barry Monk

Barry Monk received a B.S. in mathematical statistics, an M.A. in mathematics specializing in optimization and statistics, and a Ph.D. in applied mathematics, all from the University of Alabama. Dr. Monk is a professor of mathematics at Middle Georgia State University in Macon, Georgia, where he has been employed since 2001. Dr. Monk was asked to serve as program coordinator of mathematics after only two years at Macon State College; he led the development of the bachelor's degree in mathematics program and the organization of the Southeastern Scholarship Conference on E-Learning for more than 10 years. He has been teaching introductory statistics since 1992 in the classroom and online.

Need support?   We're here to help - Get real-world support and resources every step of the way.