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An introduction to mathematical statistics and its applications [electronic resource] / Richard J. Larsen, Morris L. Marx.

By: Contributor(s): Material type: TextTextPublication details: Boston : Pearson, 2018.Edition: 6th edISBN:
  • 0321693949
  • 9780134114217
Subject(s): DDC classification:
  • 519.5 22
LOC classification:
  • QA276 .L314 2012
Online resources:
Contents:
Introduction, Probability, Random Variables, Special Distributions, Estimation, Hypothesis Testing, Inferences Based on the Normal Distribution, Types of Data: A Brief Overview, Two-Sample Inferences, Goodness-of-Fit Tests, Regression, The Analysis of Variance, Randomized Block Designs, Nonparametric Statistics.
Summary: 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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Holdings
Item type Current library Call number Status Date due Barcode
E-Resources Balanga Library E-Resources 519.5 (Browse shelf(Opens below)) Available EBC00308
E-Resources Main Library E-Resources 519.5 L334 (Browse shelf(Opens below)) Available E00123

Includes bibliographical references and index.

Introduction, Probability, Random Variables, Special Distributions, Estimation, Hypothesis Testing, Inferences Based on the Normal Distribution, Types of Data: A Brief Overview, Two-Sample Inferences, Goodness-of-Fit Tests, Regression, The Analysis of Variance, Randomized Block Designs, Nonparametric Statistics.

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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