This very hands-on book helps students develop the fundamental lifelong skill of solving problems and interpreting solutions in real-world terms. Now in its third Edition, this introductory statistical book presents long-term, universal skills for students taking a one- or two-semester introductory-level statistics course. Examples include guided, explanatory solutions that emphasize problem-solving techniques.The generous collection and variety of exercises provide ample opportunity for practice and review in a variety of contexts.

This text is designed to help students fully understand the steps in basic statistical arguments, emphasizing the importance of assumptions in order to follow valid arguments or identify inaccurate conclusions.

Informazioni sull?autore

Steve Kokoska received his undergraduate degree from Boston College, and his M.S and Ph.D. from the University of New Hampshire. His initial research interests included the statistical analysis of cancer chemoprevention experiments. He has published a number of research papers in mathematics journals, including: Biometrics, Anticancer Research, and Computer Methods and Programs in Biomedicine. He has also presented results at national conferences, written several books, and been awarded grants from the National Science Foundation, the Center for Rural Pennsylvania, and the Ben Franklin Program. Steve is a long-time consultant for the College Board and conducted workshops in Brazil, the Dominican Republic, and China. He was the AP Calculus Chief Reader for four years, and has been involved with calculus reform and the use of technology in the classroom. He has been teaching at Bloomsburg University for 25years and recently served as Director of the Honors Program. Steve has been teaching introductory statistics classes throughout his academic career, and there is no doubt that this is his favorite course. This class (and text) provides students with basic, life-long, quantitative skills that they will use in almost any job and teaches them how to think and reason logically. Steve believes very strongly in data-driven decisions and conceptual understanding through problem solving.

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