Data Analysis: What Can Be Learned From the Past 50 Years [NOOK Book]

Overview

A comprehensive overview of statistical data analysis research, featuring real-world case studies and applications

How should data analysis be taught? How valid are the results? How should one deal with inhomogeneous data? What kinds of computing languages should be used, if used at all? These are but a few of the many challenging questions surrounding the fundamentals of data analysis. Data Analysis: What Can Be Learned from the Past 50 Years explores the historical and ...

See more details below
Data Analysis: What Can Be Learned From the Past 50 Years

Available on NOOK devices and apps  
  • NOOK Devices
  • Samsung Galaxy Tab 4 NOOK
  • NOOK HD/HD+ Tablet
  • NOOK
  • NOOK Color
  • NOOK Tablet
  • Tablet/Phone
  • NOOK for Windows 8 Tablet
  • NOOK for iOS
  • NOOK for Android
  • NOOK Kids for iPad
  • PC/Mac
  • NOOK for Windows 8
  • NOOK for PC
  • NOOK for Mac
  • NOOK for Web

Want a NOOK? Explore Now

NOOK Book (eBook)
$70.99
BN.com price
(Save 42%)$124.00 List Price
Note: This NOOK Book can be purchased in bulk. Please email us for more information.

Overview

A comprehensive overview of statistical data analysis research, featuring real-world case studies and applications

How should data analysis be taught? How valid are the results? How should one deal with inhomogeneous data? What kinds of computing languages should be used, if used at all? These are but a few of the many challenging questions surrounding the fundamentals of data analysis. Data Analysis: What Can Be Learned from the Past 50 Years explores the historical and philosophical implications inherent in any study of statistical data analysis. This book addresses the needs of researchers who are working with larger, complicated data sets by offering an understanding of the significance of robust data sets, the implementation of software languages, and the use of models.

Rather than focus on specific procedures, this book concentrates on general insights that can be drawn from data analysis research. The author utilizes case studies to explore the impact of technological advances on data analysis techniques and other thought-provoking issues, including:

  • Homogeneous, unstructured data

  • Statistical pitfalls

  • Singular value decomposition

  • Nonlinear weighted least squares

  • Simulation of stochastic models

  • Scatter- and curve-plots

With plentiful examples that showcase best practices for working with challenges in the field, Data Analysis is an excellent supplement for courses on data analysis, robust statistics, data mining, and computational statistics at the upper-undergraduate and graduate levels. It is also a valuable reference for applied statisticians working in the fields of business, engineering, and the life and health sciences.

Read More Show Less

Product Details

Meet the Author

Peter J. Huber, PhD, is a world-renowned statistician who has published four books and more than seventy journal articles in the areas of statistics and data analysis. He has held academic positions at Harvard University, Massachusetts Institute of Technology, Cornell University, and ETH Zurich (Switzerland), and has made significant research contributions in the areas of robust statistics, computational statistics, and strategies in data analysis. A Fellow of the Institute of Mathematical Statistics and the American Academy of Arts and Sciences, Dr. Huber is the coauthor of Robust Statistics, Second Edition, also published by Wiley.
Read More Show Less

Table of Contents

Preface.

1 What is Data Analysis?

1.1 Tukey's 1962 paper.

1.2 The Path of Statistics.

2 Strategy Issues in Data Analysis.

2.1 Strategy in Data Analysis.

2.2 Philosophical issues.

2.3 Issues of size.

2.4 Strategic planning.

2.5 The stages of data analysis.

2.6 Tools required for strategy reasons.

3 Massive Data Sets.

3.1 Introduction.

3.2 Disclosure: Personal experiences.

3.3 What is i massive? A classification of size.

3.4 Obstacles to scaling.

3.5 On the structure of large data sets.

3.6 Data base management and related issues.

3.7 The stages of a data analysis.

3.8 Examples and some thoughts on strategy.

3.9 Volume reduction.

3.10 Supercomputers and software challenges.

3.11 Summary of conclusions.

4 Languages for Data Analysis.

4.1 Goals and purposes.

4.2 Natural languages and computing languages.

4.3 Interface issues.

4.4 Miscellaneous issues.

4.5 Requirements for a general purpose immediate language.

5 Approximate Models.

5.1 Models.

5.2 Bayesian modeling.

5.3 Mathematical statistics and approximate models.

5.4 Statistical significance and physical relevance.

5.5 Judicious use of a wrong model.

5.6 Composite models.

5.7 Modeling the length of day.

5.8 The role of simulation.

5.9 Summary of conclusions.

6 Pitfalls.

6.1 Simpson's paradox.

6.2 Missing data.

6.3 Regression of Y on X or of X on Y.

7 Create order in data.

7.1 General considerations.

7.2 Principal component methods.

7.3 Multidimensional scaling.

7.4 Correspondence analysis.

7.5 Multidimensional scaling vs. Correspondence analysis.

8 More case studies.

8.1 A nutshell example.

8.2 Shape invariant modeling.

8.3 Comparison of point configurations.

8.4 Notes on numerical optimization.

References.

Index.

Read More Show Less

Customer Reviews

Be the first to write a review
( 0 )
Rating Distribution

5 Star

(0)

4 Star

(0)

3 Star

(0)

2 Star

(0)

1 Star

(0)

Your Rating:

Your Name: Create a Pen Name or

Barnes & Noble.com Review Rules

Our reader reviews allow you to share your comments on titles you liked, or didn't, with others. By submitting an online review, you are representing to Barnes & Noble.com that all information contained in your review is original and accurate in all respects, and that the submission of such content by you and the posting of such content by Barnes & Noble.com does not and will not violate the rights of any third party. Please follow the rules below to help ensure that your review can be posted.

Reviews by Our Customers Under the Age of 13

We highly value and respect everyone's opinion concerning the titles we offer. However, we cannot allow persons under the age of 13 to have accounts at BN.com or to post customer reviews. Please see our Terms of Use for more details.

What to exclude from your review:

Please do not write about reviews, commentary, or information posted on the product page. If you see any errors in the information on the product page, please send us an email.

Reviews should not contain any of the following:

  • - HTML tags, profanity, obscenities, vulgarities, or comments that defame anyone
  • - Time-sensitive information such as tour dates, signings, lectures, etc.
  • - Single-word reviews. Other people will read your review to discover why you liked or didn't like the title. Be descriptive.
  • - Comments focusing on the author or that may ruin the ending for others
  • - Phone numbers, addresses, URLs
  • - Pricing and availability information or alternative ordering information
  • - Advertisements or commercial solicitation

Reminder:

  • - By submitting a review, you grant to Barnes & Noble.com and its sublicensees the royalty-free, perpetual, irrevocable right and license to use the review in accordance with the Barnes & Noble.com Terms of Use.
  • - Barnes & Noble.com reserves the right not to post any review -- particularly those that do not follow the terms and conditions of these Rules. Barnes & Noble.com also reserves the right to remove any review at any time without notice.
  • - See Terms of Use for other conditions and disclaimers.
Search for Products You'd Like to Recommend

Recommend other products that relate to your review. Just search for them below and share!

Create a Pen Name

Your Pen Name is your unique identity on BN.com. It will appear on the reviews you write and other website activities. Your Pen Name cannot be edited, changed or deleted once submitted.

 
Your Pen Name can be any combination of alphanumeric characters (plus - and _), and must be at least two characters long.

Continue Anonymously

    If you find inappropriate content, please report it to Barnes & Noble
    Why is this product inappropriate?
    Comments (optional)