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Introduction to Mathematical Statistics and Its Applications, An - Hardcover

 
9780134114217: Introduction to Mathematical Statistics and Its Applications, An

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For courses in Mathematical Statistics


Introducing the principles of statistics and data modeling

Introduction to Mathematical Statistics and Its Applications, 6th Edition is a high-level calculus student’s first exposure to mathematical statistics. This book provides students who have already taken three or more semesters of calculus with the background to apply statistical principles. Meaty enough to guide a two-semester course, the book touches on both statistics and experimental design, which teaches students various ways  to analyze data. It gives computational-minded students a necessary and realistic exposure to identifying data models.

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For courses in Mathematical Statistics Introducing the principles of statistics and data modeling Introduction to Mathematical Statistics and Its Applications, 6th Edition is a high-level calculus student's first exposure to mathematical statistics. This book provides students who have already taken three or more semesters of calculus with the background to apply statistical principles. Meaty enough to guide a two-semester course, the book touches on both statistics and experimental design, which teaches students various ways to analyze data. It gives computational-minded students a necessary and realistic exposure to identifying data models.

Reseña del editor

For courses in Mathematical Statistics Introducing the principles of statistics and data modeling Written by famous statistician John Tukey, Introduction to Mathematical Statistics and Its Applications, 6th Edition is a high-level calculus student's first exposure to mathematical statistics. This book provides students who have already taken three or more semesters of calculus with the background to apply statistical principles. Meaty enough to guide a two-semester course, the book touches on both statistics and experimental design, which teaches students various ways to analyze data. It gives computational-minded students a necessary and realistic exposure to identifying data models.

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