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Mathematical Statistics with Applications [Hardcover]

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  • Category: Books (Mathematics)
  • Author:  Wackerly, Dennis, Mendenhall, William, Scheaffer, Richard
  • Author:  Wackerly, Dennis, Mendenhall, William, Scheaffer, Richard
  • ISBN-10:  0495110817
  • ISBN-10:  0495110817
  • ISBN-13:  9780495110811
  • ISBN-13:  9780495110811
  • Publisher:  Cengage Learning
  • Publisher:  Cengage Learning
  • Pages:  944
  • Pages:  944
  • Binding:  Hardcover
  • Binding:  Hardcover
  • Pub Date:  01-Jul-2007
  • Pub Date:  01-Jul-2007
  • SKU:  0495110817-11-SPLV
  • SKU:  0495110817-11-SPLV
  • Item ID: 102555757
  • List Price: $251.00
  • Seller: ShopSpell
  • Ships in: 2 business days
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  • Delivery by: Sep 29 to Oct 01
  • Notes: Brand New Book. Order Now.
In their bestselling title MATHEMATICAL STATISTICS WITH APPLICATIONS, premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors' use of practical applications and excellent exercises helps you discover the nature of statistics and understand its essential role in scientific research. With the addition of contributor Brendan Ames, MATHEMATICAL STATISTICS WITH APPLICATIONS now includes an enhanced eTextbook. Simulation activities using interactive applets and R embedded within the MindTap Reader help students visualize statistical concepts, and an appendix introducing students to statistical data analysis using R can be found at the end of the eTextbook.1. What Is Statistics? Introduction. Characterizing a Set of Measurements: Graphical Methods. Characterizing a Set of Measurements: Numerical Methods. How Inferences Are Made. Theory and Reality. Summary. 2. Probability. Introduction. Probability and Inference. A Review of Set Notation. A Probabilistic Model for an Experiment: The Discrete Case. Calculating the Probability of an Event: The Sample-Point Method. Tools for Counting Sample Points. Conditional Probability and the Independence of Events. Two Laws of Probability. Calculating the Probability of an Event: The Event-Composition Methods. The Law of Total Probability and Bayes''''s Rule. Numerical Events and Random Variables. Random Sampling. Summary. 3. Discrete Random Variables and Their Probability Distributions. Basic Definition. The Probability Distribution for Discrete Random Variable. The Expected Value of Random Variable or a Function of Random Variable. The Binomial Probability Distribution. The Geometric Probability Distribution. The Negative Binomial Probability Distribution (Optional). The Hypergeometric Probability Distribution. Moments and Moment-Generating Functlch
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