Continuous Univariate Distributions

Rating:
Summary: amazing content, but too many errors
Review: I agree completely with the reader from Ithaca. The last time
I used it for something important, there was a serious typo in a
formula, and much time was wasted.

Rating:
Summary: amazing content, but too many errors
Review: I agree completely with the reader from Ithaca. The last time
I used it for something important, there was a serious typo in a
formula, and much time was wasted.

Rating:
Summary: Mixed Feelings
Review: I have mixed feelings about this book.

On the positive side, it contains a wealth of useful information about a large number of continuous probability distribution functions. I use it all the time as a reference in my work. The book contains a extensive bibliography which has been useful time and time again when I need to look up things in the literature.

My first complaint is there are a number of mistakes. I realize this is a huge mass of information and mistakes are inevitable, but I found it quite unacceptable that the probability density function for the Normal distribution was incorrect. Equation 13.1 is missing a factor of sigma in the denominator. This one was quite obvious, but there have been several more subtle errors, which have caused me to waste a large amount of time searching my own work for mathematical errors, until I finally realized the source of the error was the book!

My second complaint is consistency (or lack thereof). The symbols and notation used for one distribution are not necessarily used in the same way for another distribution. This can be quite frustrating! Also, the organization from chapter to chapter (each chapter corresponds to one distribution or one distribution family) is not consistent. For example, for the Lognormal distribution, there is one section (called "Introduction") which gives the pdf of the distribution and a second section (called "Moments and Other Properties") where the moments of the distribution are listed. For the Weibull distribution, both the pdf and the moments are in one section (labeled "Definition"). This sounds like a minor point, until it comes time for you to look one of these things up!

In summary, I need this book to do my job. But I keep wishing there was another book that had the same information, but with better accuracy and organization.

Rating:
Summary: beta distribution
Review: I need to review the MLE for the parameters of Beta distribution

Rating:
Summary: Mixed Feelings
Review: Johnson and Kotz in particular continue their series of ongoing descriptions and analyses of probability/statistics distributions which is an ingenious production. They have the Creative Genius talents of summarizing, organizing, emphasizing open questions, and open mindedness to new ideas (although I have not quite tested them on some very ideas of my own). These qualities in various combinations can also be found in Allday's 1998 book in physics (which I reviewed)and Weinberg's 1974 and later books in physics (some of which I reviewed). Johnson et al. have some Creative Genius categories which are rarely found. For one thing, they cross-categorize distributions ("graphs" for the non-specialist)by their applications to real world problems, which is usually notoriously lacking in math and physics publications (beyond one or two problems). Secondly, they CHARACTERIZE distributions by various properties such as heredity (the same distribution holds for a sum of variables as for one variable, etc.), exponential derivation from other distributions, conditional expectations (I would prefer logic-based probability (LBP) expectations, but it's better than nothing), etc. In other words, their very categorization of distributions is by critical research categories and fundamental logical-factual categories, at least as far as they know them. I recommend this book and the whole series from the same authors (or at least most of them) without reservations except the ones mentioned for LBP, and I urge specialists in these fields to recommend that their students and even "laymen" (non-academic people)purchase this volume and hire a consultant or tutor to translate them or explain them in closer to ordinary English if their probability/statistical background is lacking or deficient.

Rating:
Summary: Johnson et al. (2nd Ed.) Continuous Univariate Distributions
Review: Johnson and Kotz in particular continue their series of ongoing descriptions and analyses of probability/statistics distributions which is an ingenious production. They have the Creative Genius talents of summarizing, organizing, emphasizing open questions, and open mindedness to new ideas (although I have not quite tested them on some very ideas of my own). These qualities in various combinations can also be found in Allday's 1998 book in physics (which I reviewed)and Weinberg's 1974 and later books in physics (some of which I reviewed). Johnson et al. have some Creative Genius categories which are rarely found. For one thing, they cross-categorize distributions ("graphs" for the non-specialist)by their applications to real world problems, which is usually notoriously lacking in math and physics publications (beyond one or two problems). Secondly, they CHARACTERIZE distributions by various properties such as heredity (the same distribution holds for a sum of variables as for one variable, etc.), exponential derivation from other distributions, conditional expectations (I would prefer logic-based probability (LBP) expectations, but it's better than nothing), etc. In other words, their very categorization of distributions is by critical research categories and fundamental logical-factual categories, at least as far as they know them. I recommend this book and the whole series from the same authors (or at least most of them) without reservations except the ones mentioned for LBP, and I urge specialists in these fields to recommend that their students and even "laymen" (non-academic people)purchase this volume and hire a consultant or tutor to translate them or explain them in closer to ordinary English if their probability/statistical background is lacking or deficient.