ISE Essential Statistics

3 ed
ISBN: 978-1-260-59820-9
Verlag: McGraw-Hill Education

Buch, Englisch, 658 Seiten, Gewicht: 1071 g

Essential Statistics, 3rd Edition, is designed for an introductory course in statistics. The mathematical prerequisite is basic algebra. In addition to presenting the mechanics of the subject, the authors have endeavored to explain the concepts behind them in a straightforward, clear, and engaging writing style. As practicing statisticians, the authors have done everything possible to ensure that the material is accurate and correct. This text will enable instructors to explore statistical concepts in depth yet remain easy for students to read and understand.

Autoren/Hrsg.

Navidi, William

Monk, Barry

Inhaltsverzeichnis

Chapter 1: Basic Ideas
Chapter 2: Graphical Summaries of Data
Chapter 3: Numerical Summaries of Data
Chapter 4: Probability
Chapter 5: Discrete Probability Distributions
Chapter 6: The Normal Distribution
Chapter 7: Confidence Intervals
Chapter 8: Hypothesis Testing
Chapter 9: Inferences on Two Samples
Chapter 10: Tests with Qualitative Data
Chapter 11: Correlation and Regression

Über Autor(innen)

Monk, Barry
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.

Navidi, William
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.