I stumbled on this text while trying to understand nested design for analysis of variance. Better than any other text I used, this book helped me to understand the calculation steps as well as the underlying theory. (All the other texts I used had holes in their explanation.) This has become my favorite statistics reference.

Excellent presentation of complicated subject. For many people stats are intimidating. This book is the clearest presentation I've seen

This is a very new and unique book that covers the gamut of statistical issues through all phases of drug development. Shao is a distinguished professor from Wisconsin and Chow teaches at Temple but is known for his long career in the pharmaceutical industry.

The book is good for biostatisticians and regulatory affairs specialists as a reference source. All the key statistical issues are addressed and the reader is given the perspective of the ICH and FDA guidance documents. The underlying statistical methodology that justifies the recommendations in the guidances is presented. This is a state-of-the-art book. Shao and Pigeot produced some of the recent research in individual bioequivalence that established a bootstrap procedure as an appropriate way to construct confidence intervals for the problem. Their method is recommended in an FDA guidance document.

But more than just this one example, all the key issues that have been the subject of FDA workshops over the past several years are addressed in this book. These topics include calibration, assay and assay validation, dissolution testing, stability analysis, shelf life estimation, bioequivalence, randomization and blinding, what constitutes substantive evidence in clinical development, therapeutic equivalence and noninferiority, Bayesian approaches in clinical trials, problems involving missing and incomplete data, longitudinal methods, meta-analysis, quality of life studies and instrument validation, and medical imaging.

Other prevalent issues in clinical trials include group sequential methods, hierarchical Bayesian models and multiple testing. These issues are not covered as much in this text as the others we have mentioned. But there is some discussion of multiplicity in the context of quality of life studies. An example of sequential testing is used to illustrate model selection in Chapter 2. The important issues of design and sample size requirements are presented throughout the book.

While not all topics are covered in sufficient depth, the book is remarkable in the breadth of material covered in just 350 pages of text. The authors also provide a very authoritative list of references and regulatory guidances and other documents.

Statistics can be a very boring subject. Most of us remember, at one time or another, taking a statistics course. One thing we all remember very well is not wanting to look at let alone read our statistics texts. Dr. Blaisdell transforms this extraordinarily dry subject into an interesting medley of mean median a la mode. Definitely recommended to any instructor trying to reduce the number of students who drop their class....

This book is a MUST for people who thought they had understood statistics, but need to refresh their knowledge. It is structured as questions and answers throughout, and is easy to comprehend.

I use it as the recommended book for all my "statistics for beginners" classes around the world.

I thought it was a pretty good book, for my purposes. It is a collection of academic like articles by different statisticians working in the area of sports modelling and each author wrote one chapter on the sport or topic of his expertise. I found it easier to read than most academic articles. All the chapters I've read so far (4 or 5) have provided me with 1 to 4 ideas that I might be able to apply to my own modelling of sporting events. So for me it was a good buy.

I purchased STATISTICS IN THE 21 CENTURY because of a recommendation from a statistics listserv for which I subscribe. I thought this monograph would help me with my undergraduate teaching duties. Well, it didn't. Thus, if that's your objective, don't buy it.

If you're interested in seeking the board range of directions for applied statistics, this is your book. In my disappointment in realizing that this book is not what I thought it would be, I read it anyway. It is quite well written. For me, I thought I would only be interested in the social science section, but I found some of the Engineering and Physicial Science chapters helpful. All the chapters are quite insightful.

The only disappointing aspect of the monograph was the incomplete information on the autocorrelation debate for time series data. I wanted to know more.

Otherwise, it is a nice set of statistical readings.

This text is easy to understand and read. It goes about the topic of statistics in a different manner than other stat books do. Wardrop explains the topics in real life situations, applicable to what one may really encounter without being a statistics major. I am lucky in that I was able to take the course with Prof. Wardrop and use his book. I took a different stat course earlier but dropped it because the professor and the text in that course were both confusing and boring. Also the information and method of which we were learning was both impractical and frustrating. I would recommend Wardrop and his text over others.

This cutting-edge textbook on the Statistics of the Galaxy Distribution describes and predicts the pattern forming habits, distribution laws, and spatial resolutions of the large-scale cosmological structures in the universe. Galaxies, clusters, superclusters, walls of galaxies, filamentary regions, voids, and dark matter areas are discussed. Not only does the book detail the astrophysical natures of these physical structures but it also uses recent developments in statistics in order to predict that which cannot be known absolutely from mere astronomical observation. Cosmological point processes and continuous random fields are stochastic (random) processes outlined in the book. They describe the frequency of the originating matter in the universe that distributes itself in a mode that represents the harmonics of space. Some of the geometry used in the book is non-Euclidean because the large regions of space that are being assesed reside where space-time curvature is accounted for.

Periodic sollutions for cosmological fields, such as spectras for Gaussian random fields, are modelled with "gradient topographies", as waveforms, using Fourier transforms. The digital imaging of reallized spectra, the Boolean grain model for Poisson distribution, cosmological simulation for a percolating cluster, and the redshift survey for voids are pretty cool.

This book tackles a wide range of mathematical topics and applies areas of very pertinent, recent fields of scientific inquiry. The void probability function, fractal properties of the galaxy distribution, fractal models for the univesre, Hausdorff dimension (in relation to sets of fractioned dimension), correlation lenghth and fractal behaviour, multifractal measures (very interesting), the Voronoi model of tesselations (a crystalline structure of galaxy distribution composed of cellular geometry), Fourier analysis of clustering, random fields and point processes, redshift distortions, pencil-beams and slices, and an awesome section devoted to cosmography includes areas on time machines, gravitational lensing, cosmic shear etc. also topological measurements, Minkowski functionals, cluster and percolation analysis, spaning trees, wavelets, void statistics, supergalactic coordinate systems, it's a very versatile cosmology text.

The specificity of subject this book examines is a very fascinating and important one. The way the universe disperses matter and organizes itself spatially, on a large-scale, may soon give clues to the general unified theory of physical fields, as information correlations for small-scale distributions. Observing the surveys of the largest fields reveal that the patterns for galaxy distribution form a network resembling nothing else but the axonal webbing of the brain.

For any fascinated students, scientists or mathematicians, this book provides valuable knowledge about the universe. If this was all you understood about cosmology you would be closer to absolute cosmological knowledge than a cosmologist who knew nothing but general theory.

Other recommendations would be; Towards the Edge of the Universe by Stuart Clark, Galactic Astronomy by James Binney and Astrometry of Fundamental Catalogues by H.G. Walter

I bought this book because it was required reading for my second year statistics course (Michael Smithson is actually my stats lecturer at the moment!) but I was certainly not disappointed. The title "Statistics with Confidence" is true to its name - I am SO much better and more confidence with statistics now then I was at the beginning of the year and I am actually enjoying it!!!

His explanations are brilliant and easy to follow and understand and his examples and practice questions are never few, so there's always more to keep you busy and entertained!

His book also comes with a CD-Rom which incldues very easy to use programs and examples to help you practice.

Buy this book if you are looking for a great and easy to understand overview of Psychology related Statistics (or even statistics in general) as either a supplement to your current texts or alone - and at such a good price, you'd be mad not to!