---
product_id: 20361734
title: "Reading and Understanding More Multivariate Statistics"
brand: "laurence g. grimmpaul r. yarnold"
price: "₨1914"
currency: SCR
in_stock: true
reviews_count: 10
url: https://www.desertcart.sc/products/20361734-reading-and-understanding-more-multivariate-statistics
store_origin: SC
region: Seychelles
---

# Reading and Understanding More Multivariate Statistics

**Brand:** laurence g. grimmpaul r. yarnold
**Price:** ₨1914
**Availability:** ✅ In Stock

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- **What is this?** Reading and Understanding More Multivariate Statistics by laurence g. grimmpaul r. yarnold
- **How much does it cost?** ₨1914 with free shipping
- **Is it available?** Yes, in stock and ready to ship
- **Where can I buy it?** [www.desertcart.sc](https://www.desertcart.sc/products/20361734-reading-and-understanding-more-multivariate-statistics)

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- laurence g. grimmpaul r. yarnold enthusiasts

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## Description

Reading and Understanding More Multivariate Statistics

## Images

![Reading and Understanding More Multivariate Statistics - Image 1](https://m.media-amazon.com/images/I/410skVUqTeL.jpg)
![Reading and Understanding More Multivariate Statistics - Image 2](https://m.media-amazon.com/images/I/31sP99gWO-L.jpg)

## Customer Reviews

### ⭐⭐⭐⭐ 







  
  
    Multivariate Measurement
  

*by J***D on Reviewed in the United States on April 30, 2012*

Lawrence Grimm and Paul Yarnold's edited collection of chapters about multivariate methods used in developing measurement scales is a companion volume to their previously-published volume, 
  
Reading and Understanding Multivariate Statistics







  
  
    , that introduces multivariate statistical methods more generally.The editors have a clear vision for their book.  "Like its predecessor, this volume does not portend to teach readers how to actually perform the statistical procedures discussed."  Its aim is to `...present the fundamental conceptual aspects of common multivariate techniques and... the assumptions, statistical notations, and research contexts within which the analyses are often used."  Their target audience is the research consumer rather than the practitioner.There are two types of chapters.  One type introduces and explores basic measurement concepts, including levels of measurement, scale reliability, and establishing validity using the most appropriate evidence.  Most chapters are of the second type, showing readers how to interpret the results of a specific method.  The methods covered are cluster analysis, Q-technique factor analysis, structural equation modeling, canonical correlation, multivariate analysis of variance, and survival analysis.The chapters are clearly written and each contain helpful instructional features such as thoroughly-elaborated examples, glossaries, and recommended readings.  There is a clear advantage to focusing the resources at the chapter, rather than the book level.  It is easy to use it as a reference for a single technique without searching through the rest of the book to string together related information.Grimm and Yarnold's book is recommended for anyone who needs to understand research using these multivariate methods.

### ⭐⭐⭐⭐⭐ 







  
  
    Just as good as the first
  

*by A***R on Reviewed in the United States on August 22, 2020*

Like the first book, this book simply and concisely teaches you statistics. This book and the one that comes before it are two of my favorite statistic books. It makes statistics so easy and makes me more confident in my statistics knowledge. I am really math-phobic so this book was very helpful for me.

### ⭐⭐⭐ 







  
  
    Fair discussion of newer tools
  

*by K***R on Reviewed in the United States on March 31, 2011*

The treatment of newer statistical tools (multivariate analyses) is covered in this book, with different authors writing the different parts.  This can help to keep the material fresh, but it also gives each section a disjointed feel, as some sections are very long and comprehensive and others are quite short.  The book makes a case for using newer tools such as cluster analysis in place of some other typically-used tools (e.g., discriminant analysis, factor analysis) as a fresher approach; This is fine because many dissertations and published studies are using more and more qualitative methods (or mixed methods) these days, but it should put them into context - no cluster analysis will ever be as robust as a factor analysis.

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*Product available on Desertcart Seychelles*
*Store origin: SC*
*Last updated: 2026-03-07*