In this 3rd edition revised text, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, and an explanation of intuition and ideas behind the statistical methods. Concepts are motivated, illustrated and explained in a way that attempts to increase one's intuition. To quote from the preface, "It is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data."
Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions and examples.
Applications and examples refer to real-world issues, such as gun control, stock price models, health issues, driving age limits, school admission ages, use of helmets, sports, scientific fraud and many others.
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- Companion Website w/Data Sets - http://www.elsevierdirect.com/companion.jsp?ISBN=9780123743886
- Unique historical perspective profiling prominent statisticians and historical events to motivate learning by providing interest and context
- Use of exercises and examples helps guide the student towards indpendent learning using real issues and real data, e.g. stock price models, health issues, gender issues, sports, scientific fraud.
- Summary/Key Terms- chapters end with detailed reviews of important concepts and formulas, key terms and definitions which are useful to students as study tools
- Data sets from text and exercise material will be available to download from the text website, saves students time
This text is written for the introductory non-calculus based statistics course offered in mathematics and/or statistics departments for undergraduate students of any major who take a semester course in basic Statistics or a year course in Probability and Statistics.
Introduction to Statistics
Describing Data Sets Using Statistics to Summarize
Data Sets Probability
Discrete Random Variables
Normal Random Variables
Distributions of Sampling
Statistics Estimation Testing
Hypothesis Tests Concerning Two Populations
Analysis of Variance Linear Regression
Chi-Squared Goodness of Fit Tests
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- © Academic Press 2010
- 11th February 2010
- Academic Press
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Sheldon M. Ross is a professor in the Department of Industrial Engineering and Operations Research at the University of Southern California. He received his Ph.D. in statistics at Stanford University in 1968. He has published many technical articles and textbooks in the areas of statistics and applied probability. Among his texts are A First Course in Probability, Introduction to Probability Models, Stochastic Processes, and Introductory Statistics. Professor Ross is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences. He is a Fellow of the Institute of Mathematical Statistics, and a recipient of the Humboldt US Senior Scientist Award.
University of Southern California, Los Angeles, USA