A Student's Guide to Analysis of Variance Review

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A Student's Guide to Analysis of Variance ReviewAs someone who has read many books covering this topic (e.g., Neter et al., Kirk) I strongly recommend reading this book! This book is particularly useful if you are taking or have had courses covering analysis of variance (ANOVA). Even for the mathematically sophisticated reader it is easy to walk away with a fuzzy, unclear understanding of the uses of ANOVA techniques (sad but true). This book explains how to use these by parsimoniously explaining the conceptual foundations of ANOVA. The books links statistical concepts to the variety of formulas and inferential techniques one encounters, such as two-way and mult-way ANOVAs, interaction, testing of simple effects.A Student's Guide to Analysis of Variance OverviewIn the investigation of human behaviour, statistical techniques are employed widely in the social sciences. Whilst introductory statistics courses cover essential techniques, the complexities of behaviour demand that more flexible and comprehensive methods are also employed. Analysis of Variance (ANOVA) has become one of the most common of these and it is therefore essential for both student and researcher to have a thorough understanding of it.A Student's Guide to Analysis of Variance covers a range of statistical techniques associated with ANOVA, including single and multiple factor designs, various follow-up procedures such as post-hoc tests, and how to make sense of interactions. Suggestions on the best use of techniques and advice on how to avoid the pitfalls are included, along with guidelines on the writing of formal reports.Introductory level topics such as standard deviation, standard error and t-tests are revised, making this book an invaluable aid to all students for whom ANOVA is a compulsory topic. It will also serve as a useful refresher for the more advanced student and practising researcher.

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Statistics Explained: A Guide for Social Science Students, 2nd Edition Review

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Statistics Explained: A Guide for Social Science Students, 2nd Edition ReviewThe only topics missing from this book that I wish had been discussed are validity (concurrent, longitudinal predictive, diagnostic) and item analysis (difficulty and discrimination indexes). A few pages are devoted to reliability, but I would have liked to see more detailed discussion devoted to the differences between the types of reliability measurement (test-retest, split halves, and parallel forms reliability).
These minor points aside, this book is a wonderfully readable and not at all intimidating introduction to statistics. Highly recommended!Statistics Explained: A Guide for Social Science Students, 2nd Edition OverviewStatistics Explained clearly outlines the major statistical tests used by undergraduates in the social sciences. It provides easy-to-understand explanations of how and why they are used and makes statistics much less mysterious. This book:Is a simple introduction to the jargonShows you when to be sceptical about statisticsGuides you in using computers in statistical analysis. Statistics Explained can be dipped into so that readers can see why a specific analytical procedure was developed and what it is best used for. Readers can also analyse their own data by following the worked examples provided. People who understand statistics are not unusual. Anyone can do it. In this book, Perry Hinton shows that statistics can be a logical and helpful tool to all of us in deciding answers to our research questions. Statistics Explained will be warmly welcomed by students at all levels, and by the lecturers who struggle to teach them.

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Applied Linear Regression Models- 4th Edition with Student CD (McGraw Hill/Irwin Series: Operations and Decision Sciences) Review

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Applied Linear Regression Models- 4th Edition with Student CD (McGraw Hill/Irwin Series: Operations and Decision Sciences) ReviewThis book if not for business majors , engineering students and psycology students.
This is an EXCELLENT book for statistics undergrad/grad and PhD students.
I spent over 10 hours weekly just reading the book every week. Plus my assignments will take another 10 hours . So be prepared for a 20 hr week.
YOU NEED TO TAKE A BASIC STAT / INTRO STAT course before this. If you dont know the meaning of P-values , T-test , F-test , DO NOT TAKE THIS COURSE. This book will not introduce you to those things. Unfortunately many buiness schools ( including top 10 ) dont offer a good intro stat course, so buiness majors jumping in to this course is a wrong idea.
This book is also a "good to own book". The first 15 or so chapters has regression and the second half ( next 15 chapters ) has DOE (design of experiments). GREAT BOOK !
One piece of advice - make sure you learn to use SAS with this course . In real world applications many industries are using SAS. Even if your teacher insists on using R package / splus , YOU MAKE SURE YOU know how to do those things in SAS . There is a SAS student manual with this book, specially written for this book . buy it ISBN - 0-07-302177-6
good luck !
Applied Linear Regression Models- 4th Edition with Student CD (McGraw Hill/Irwin Series: Operations and Decision Sciences) Overview
Thoroughly updated and more straightforward than ever, Applied Linear Regression Models includes the latest statistics, developments, and methods in multicategory logistic regression; expanded treatment of diagnostics for logistic regression; a more powerful Levene test; and more. Cases, datasets, and examples allow for a more real-world perspective and explore relevant uses of regression techniques in business today.


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