Skip to main content
Elsevier

Introductory Statistics

Introductory Statistics, Third Edition, presents statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedure… Read more

Data Mining & ML

Unlock the cutting edge

Up to 20% on trusted resources. Build expertise with data mining, ML methods.

Explore now

Description

Introductory Statistics, Third Edition, presents statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also to understand why these procedures should be used. This book offers a unique historical perspective, profiling prominent statisticians and historical events in order to motivate learning.

To help guide students towards independent learning, exercises and examples using real issues and real data (e.g., stock price models, health issues, gender issues, sports, scientific fraud) are provided. The chapters end with detailed reviews of important concepts and formulas, key terms, and definitions that are useful study tools. Data sets from text and exercise material are available for download in the text website.

This text is designed for introductory non-calculus based statistics courses that are offered by mathematics and/or statistics departments to undergraduate students taking a semester course in basic Statistics or a year course in Probability and Statistics.

Key features

  • 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













Readership

Undergraduates in mathematics and/or statististics or students with a one-semester statistics or two-semster probability and statistics requirement.

Table of contents

Preface

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

Statistical Hypotheses

Hypothesis Tests Concerning Two Populations

Analysis of Variance Linear Regression

Chi-Squared Goodness of Fit Tests

Nonparametric Hypotheses

Tests

Quality Control

Appendices

Product details

About the author

SR

Sheldon M. Ross

Dr. Sheldon M. Ross is a professor in the Department of Industrial and Systems Engineering at the University of Southern California. He received his PhD 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, a Fellow of INFORMS, and a recipient of the Humboldt US Senior Scientist Award.
Affiliations and expertise
Professor, Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, USA

View book on ScienceDirect

Read Introductory Statistics on ScienceDirect