The range of readily accessible statistical methods has greatly expanded over the past decade, particularly with the growing accessibility of comprehensive statisti cal computing packages. The approach adopted in this book has anticipated the changes by its emphasis on building understanding and skills in method selection and interpretation of findings.
There has been a reduction in computational for mulas to reflect the fact that basic statistical analyses are now almost universally undertaken on computers. This has allowed the inclusion of a more general cover age of unifying methodology, particularly Generalized linear methodology, which permits users to more accurately match their requirements to statistical models and methods. A major addition is a chapter on the commonly used multivariate methods. The Experimenters View. Comparing Model and Data.
The approach adopted in this book has anticipated the changes by its emphasis on building understanding and skills in method selection and interpretation of findings.
A major addition is a chapter on the commonly used multivariate methods. As such, even a student of statistics can benefit very much from this book. Although the book is not that big, it contains lots of valuable information. The author has really accomplished showing that statistics should be seen as an integral component of investigation and as a tool for conducting a well-informed post-mortem of data! The author has produces a masterpiece.
His book can be used as a reference and as an undergraduate text for a course in statistics for those taking statistics as a service course as well as majors. As a reference manual, it is useful because it contains statistical methods from a wide spectrum starting with univariate statistical methods to multivariate statistical methods.
Specialized vocabulary is defined and used in context, and concepts are clearly explained. I like how the end-of-chapter quizzes require students to integrate concepts highlighted in a given chapter with relevant information from previous chapters.
Statistics Translated: A Step-by-Step Guide to Analyzing and Interpreting Data
The graphics visually build statistical concepts on one another—I particularly like the continued use of the sample distributions and how they are tied to use of normal curve assumptions. These are serious omissions in many texts.
The book is well situated to inform upper-level undergraduate and graduate students pursuing practitioner-related degrees. It does a good job of laying out a framework for inquiry and aligning statistical reasoning and tools with this framework.
Recommended for you
It is written for an audience who may do some basic statistical calculations and analysis, but who primarily will be consumers of statistics and quantitative research. I will recommend this text to colleagues who teach statistics or more general research methods courses for this audience. His explanations reveal the mysteries behind inferential statistics as he describes how to think statistically. Readers will discover the connections among the hypothesis, dependent measures, selection of appropriate inferential statistical analysis procedures, and how to interpret the evidence.
- Silanes and other coupling agents. / Volume 4.
- How to Learn Statistics for Data Science, The Self-Starter Way.
- About This Item.
- Costly Giving, Giving Guaizas: Towards an organic model of the exchange of social valuables in the Late Ceramic Age Caribbean.
- Morning Songs, Op. 133, No. 2.
The detailed, step-by-step directions on how to conduct statistical tests using SPSS are a plus; Terrell teaches both theory and practice. It is easy to understand, surprisingly practical, and comprehensive. Most important, Terrell directly addresses the most common analysis question that I hear from my own students: 'How do I know which statistical analysis to use?
It does a better job than other available texts of expressing the core ideas through words, rather than numbers. The material is presented well and I like that it is broken up into small parts. Research methods and data collection techniques are integrated effectively. This is one statistics text that students will want to keep on their bookshelves rather than sell at the end of the semester.