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21 of 21 people found the following review helpful:
4.0 out of 5 stars
statistics without mathematical formulas, November 24, 2001
As a computer software developer who has worked in a high tech manufacturing environment, I was exposed to statistical topics on a daily basis. I always got by without any problems, but I always regretted not taking a formal statistics class. Given the positive reviews here, I purchased this book, thinking it would be a magic bullet. It isn't. I was sorely disappointed in the depth (and length) of the text. However, the author achieves what he sets out to do -- create a readable statistics book without any mathematical formulas. Rowntree's text does provide a good overview in very general and broad terms on statistical topics in layman's terms. It is consciously targeted towards non-mathematicians, and provides a great resource for understanding basic statistical topics. This book is for people who must casually digest and interpret statistics, and not for those of us who need to produce them. This thin paperback is a relatively quick read. There are no exercises, just descriptive examples woven into the text, punctuated by a few questions. Reading this won't make you pass a statistics final, nor will it make you an expert. It will, however, introduce you to a high level view of statistics.
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31 of 35 people found the following review helpful:
5.0 out of 5 stars
Contents of the Book, February 17, 2004
(The "Search Inside the Book" feature was not available for this book at the time this review was posted) One of the things that help me decide whether or not to buy a book is the table of contents. I hope the information below is useful. Introduction. How to use this book. 1. Statistical inquiry. Making sense of experience. What is statistics? Descriptive and inferential statistics. Collecting a sample. 2. Describing our sample. Statistical variables. Error, accuracy and approximations. 3. Summarizing our data. Tables and diagrams. Central tendency (averages). Measures of dispersion. 4. The shape of a distribution. Skewed distributions. Introducing the normal distribution. Proportions under the normal curve. Comparing values. 5. From sample to population. Estimates and inferences. The logic of sampling. A distribution of sample-means. Estimating the population-mean. Estimating other parameters. 6. Comparing samples. From the same or different populations? Significance testing. The significance of significance. Comparing dispersions. Non-parametric methods. 7. Further matters of significance. One- versus two-tailed tests. z-tests and t-tests. Comparing several means. Comparing proportions. 8. Analysing relationships. Paired values. Three kinds of correlation. The strength of a correlation. The significance of a correlation coefficient. Interpreting a correlation coefficient. Prediction and regression. Postscript. Review. Caution. Bibliography. Index.
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10 of 10 people found the following review helpful:
5.0 out of 5 stars
"Without Tears" but WITH Value, November 9, 1997
The text is the first I've found that speaks about statistics in truly lay terms. No Carl Sagan, the author nonetheless brings a difficult--and potentially boring--subject to the masses. Okay, not the masses. Let's just say, the interested. I teach a Stats course in a large M.B.A. program; I recommend this book to all my students.
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