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“The text is highly readable, and the author has done a good job making difficult topics like path analysis easy for students to comprehend. As much as possible, the author uses simple language and explains things in ways that students would be able to grasp. His incorporation of numerous examples helps to facilitate this goal as well.”
“The key strengths of this text are is applied perspective, focusing on conceptual understanding of data analyses rather than arcane statistical proofs. It finds just the right balance of technical, conceptual and practical perspectives. In addition, the heavy reliance on real-world examples and supplemental information in appendices will render it an invaluable resource for young graduate students as they progress in their research training.”
“This is a breath of fresh air compared to most statistics texts—rigorous but highly readable. The author does an impressive job of making statistical concepts feel intuitive. In addition, the integration of datasets and SPSS problems to solve make this book unique.”
A well written book that provides a wonderful coverage of a range of key statistical concepts. Particularly useful for regression analysis as it covers variants of this method that are rarely seen in other statistics books for the same audience. I am not adopting this book however as apart from this it adds very little over and above what is currently being used by my students, the interactive SPSS data sets and screenshots are also a little dated by comparison. A very good book, just doesn't do enough different for it to be adopted.
This is an excellent textbook but for our purposes this would be more suitable on a postgraduate level.
Clearly written with essential chapters on more advanced topics (appropriate use of ANCOVA; path analysis). Recommended for graduate students in clinical psychology.
The following review regards the book “Intermediate Statistics a Conceptual Course” by Brett W. Pelham.
There are many textbooks about statistics. The first question we should answer is whether all these books are necessary or not. To my point of view the answer is YES and I will explain why.
This book is well-written and covers a range of important statistical methods. However, I would have preferred more emphasis on the mathematics and less on SPSS (even though I realise that students have a tendency to rely heavily upon the programme).
I consider this book as the next in line after digesting Neil Salkind book - Statistics for people who hate statistics. I would recommend this book to Geography post-graduates given that the conceptual approach adopted in this book.
The book is userfriendly, with examples/hypothetical studies that are very helpful and entertaining, making statistical analysis almost fun for a non-statistician. Although we do not use SPSS statistics software programming for our data analysis, the syntax and examples provided are very helpful.
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