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John E. Freund's Mathematical Statistics with Applications, 8th edition

Published by Pearson (March 15, 2018) © 2019

  • Irwin Miller
  • Marylees Miller

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For 2-semester or 3-quarter calculus-based courses in Introduction to Mathematical Statistics. Can also be used for a 1-semester course emphasizing probability, probability distributions and densities, sampling, and classical statistical inference.

A modern classic

John E. Freund's Mathematical Statistics with Applications, 8th Edition provides a calculus-based introduction to the theory and application of statistics, based on comprehensive coverage that reflects the latest in statistical thinking, the teaching of statistics, and current practices.

This title is part of the Pearson Modern Classics series. Pearson Modern Classics are acclaimed titles at a value price.

Hallmark features of this title

  • The Theory in Practice sections at the end of every chapter give students the chance to apply the methods they've learned.
  • More than 1200 exercises offer a wide variety to choose from in creating assignments, tests, and class work.
    • Many of these exercises offer the opportunity to use technology so that students can understand the role of computers in factoring and analyzing statistical data.
  • Comprehensive coverage of statistical theories students have appreciated for generations.
  • Comprehensive appendices summarize the properties of the special probability distributions and density functions, making this text an invaluable reference.

New and updated features of this title

  • The clear writing style is Freund's legacy, and has been carefully revised for today's students.
  • Learning aids throughout this text support students in their studies.
    • These include formal presentations of Definitions and enhancements in the emphasis of Theorems, Definitions, and Examples.

Brief Contents

  1. Introduction
  2. Probability
  3. Probability Distributions and Probability Densities
  4. Mathematical Expectation
  5. Special Probability Distributions
  6. Special Probability Densities
  7. Functions of Random Variables
  8. Sampling Distributions
  9. Decision Theory
  10. Point Estimation
  11. Interval Estimation
  12. Hypothesis Testing
  13. Tests of Hypotheses Involving Means, Variances, and Proportions
  14. Regression and Correlation
  15. Design and Analysis of Experiments
  16. Nonparametric Tests

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