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Intuitive Introductory Statistics

  • Textbook
  • © 2017

Overview

Authors:
  1. Douglas A. Wolfe

    1. Department of Statistics, The Ohio State University, Columbus, USA

    View author publications

    You can also search for this author in PubMed   Google Scholar

  2. Grant Schneider

    1. Upstart Network, San Carlos, USA

    View author publications

    You can also search for this author in PubMed   Google Scholar

  • Unique approach that includes novel topics for introductory courses, including: bootstrapping, Walsh averages, and jackknifing
  • Engaging examples and exercises draw readers in and facilitate work by hand and with calculators and statistical software
  • Designed for use inside and outside statistics departments
  • Accompanying data sets and R code make this textbook easy to use for students and instructors
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Texts in Statistics (STS)

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Table of contents (12 chapters)

  1. Front Matter

    Pages i-xviii
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  2. Exploratory Data Analysis: Observing Patterns and Departures from Patterns

    • Douglas A. Wolfe, Grant Schneider
    Pages 1-142

  3. Exploring Bivariate and Categorical Data

    • Douglas A. Wolfe, Grant Schneider
    Pages 143-198

  4. Designing a Survey or Experiment: Deciding What and How to Measure

    • Douglas A. Wolfe, Grant Schneider
    Pages 199-241

  5. Understanding Random Events: Producing Models Using Probability and Simulation

    • Douglas A. Wolfe, Grant Schneider
    Pages 243-330

  6. Sampling Distributions and Approximations

    • Douglas A. Wolfe, Grant Schneider
    Pages 331-415

  7. Statistical Inference: Estimating Probabilities and Testing and Confirming Models

    • Douglas A. Wolfe, Grant Schneider
    Pages 417-535

  8. Statistical Inference for the Center of a Population

    • Douglas A. Wolfe, Grant Schneider
    Pages 537-631

  9. Statistical Inference for Matched Pairs or Paired Replicates Data

    • Douglas A. Wolfe, Grant Schneider
    Pages 633-668

  10. Statistical Inference for Two Populations–Independent Samples

    • Douglas A. Wolfe, Grant Schneider
    Pages 669-771

  11. Statistical Inference for Two-Way Tables of Count Data

    • Douglas A. Wolfe, Grant Schneider
    Pages 773-837

  12. Statistical Inference for Bivariate Populations

    • Douglas A. Wolfe, Grant Schneider
    Pages 839-905

  13. Statistical Inference for More Than Two Populations

    • Douglas A. Wolfe, Grant Schneider
    Pages 907-945

  14. Back Matter

    Pages 947-976
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Keywords

About this book

This textbook is designed to give an engaging introduction to statistics and the art of data analysis. The unique scope includes, but also goes beyond, classical methodology associated with the normal distribution. What if the normal model is not valid for a particular data set? This cutting-edge approach provides the alternatives. It is an introduction to the world and possibilities of statistics that uses exercises, computer analyses, and simulations throughout the core lessons. These elementary statistical methods are intuitive. Counting and ranking features prominently in the text. Nonparametric methods, for instance, are often based on counts and ranks and are very easy to integrate into an introductory course.​ The ease of computation with advanced calculators and statistical software, both of which factor into this text, allows important techniques to be introduced earlier in the study of statistics. This book's novel scope also includes measuring symmetry with Walsh averages, finding a nonparametric regression line, jackknifing, and bootstrapping​. Concepts and techniques are explored through practical problems. Quantitative reasoning is at the core of so many professions and academic disciplines, and this book opens the door to the most modern possibilities.

Authors and Affiliations

  • Department of Statistics, The Ohio State University, Columbus, USA

    Douglas A. Wolfe

  • Upstart Network, San Carlos, USA

    Grant Schneider

About the authors

Douglas A. Wolfe is a Professor Emeritus in the Department of Statistics at The Ohio State University. Much of his current research is in ranked set sampling. He is also the author of a popular textbook on nonparametric statistics. Grant Schneider is a Data Scientist at Upstart Network in the San Francisco Bay area. Grant created the accompanying R package and is experienced with statistical programming for research and in the classroom. He received his PhD in Statistics from The Ohio State University.

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