This title offers instructors an effective way to teach the essentials of statistics, including early coverage of Regression, within a more limited time frame.

Reflecting Cengage Learning's commitment to offering value for students, these new hybrid versions feature the same content and coverage found in the full text while delivering end-of-section exercises online in Aplia. Access to Aplia is included with every new text, giving you an interactive learning experience with the convenience of a text that is both brief and affordable.UNDERSTANDABLE STATISTICS: CONCEPTS AND METHODS, Hybrid Package, Tenth Edition, is a thorough, yet accessible program designed to help readers overcome their apprehensions about statistics. The authors provide clear guidance and informal advice while showing the links between statistics and the world, while offering the convenience of a more brief and more affordable text. To reinforce this approach--and make the material interesting as well as easier to understand--the book integrates real-life data from a variety of sources, including journals, periodicals, newspapers, and the Internet. Readers also have opportunities to develop their critical thinking and statistical literacy skills through special features and exercises throughout the text. The use of graphing calculators, Excel®, MINITAB®, and SPSS® is covered for those who wish to learn about these helpful tools.

Want to be sure that your answers are correct and that you took the correct steps to arrive at them? This manual, which contains fully worked-out solutions to all of the odd-numbered exercises in the text, allows you to do so.

Want to be sure that your answers are correct and that you took the correct steps to arrive at them? This manual contains fully worked-out solutions for all odd-numbered exercises in the text, so you can check your answers and understand how to solve even the toughest problems.

An Introduction to Modern Astrophysics is a comprehensive, well-organized and engaging text covering every major area of modern astrophysics, from the solar system and stellar astronomy to galactic and extragalactic astrophysics, and cosmology. Designed to provide students with a working knowledge of modern astrophysics, this textbook is suitable for astronomy and physics majors who have had a first-year introductory physics course with calculus. Featuring a brief summary of the main scientific discoveries that have led to our current understanding of the universe; worked examples to facilitate the understanding of the concepts presented in the book; end-of-chapter problems to practice the skills acquired; and computational exercises to numerically model astronomical systems, the second edition of An Introduction to Modern Astrophysics is the go-to textbook for learning the core astrophysics curriculum as well as the many advances in the field.

"In formulating a stochastic model to describe a real phenomenon, it used to be that one compromised between choosing a model that is a realistic replica of the actual situation and choosing one whose mathematical analysis is tractable. That is, there did not seem to be any payoff in choosing a model that faithfully conformed to the phenomenon under study if it were not possible to mathematically analyze that model. Similar considerations have led to the concentration on asymptotic or steady-state results as opposed to the more useful ones on transient time. However, the relatively recent advent of fast and inexpensive computational power has opened up another approach--namely, to try to model the phenomenon as faithfully as possible and then to rely on a simulation study to analyze it"--

[The authors] have written this text to make statistics accessible to everyone, including those with a limited mathematics background. [The book] emphasizes concepts of statistics. Statistical methods are carefully presented with a focus on understanding both the suitability of the method and the meaning of the result. Statistical methods and measurements are developed in the context of applications.-Pref.