Statistics basic concepts

D. R. Cox, P/anning of Experiments,]ohxi Wiley Sons, Inc., New York, 1958. This book provides a simple survey of the principles of experimental design and of some of the most usehil experimental schemes. It tries "as far as possible, to avoid statistical and mathematical technicalities and to concentrate on a treatment that will be intuitively acceptable to the experimental worker, for whom the book is primarily intended." As a result, the book emphasizes basic concepts rather than calculations or technical details. Chapters are devoted to such topics as "Some key assumptions," "Randomization," and "Choice of units, treatments, and observations."... 

It is recommended at this stage of the text that the reader unfamiliar with the basic concepts of variation and process capability refer to Appendix I for an introductory treatise on statistics, and Appendix II for a discussion of process capability studies. 

Haugen, E. B. 1982a Modern Statistical Materials Selection - Part 1 Some Basic Concepts. Materials Engineering, 96, July, 21-25. 

Correctly used, statistics is an essential tool for the analyst. The use of statistical methods can prevent hasty judgements being made on the basis of limited information. It has only been possible in this chapter to give a brief resume of some statistical techniques that may be applied to analytical problems. The approach, therefore, has been to use specific examples which illustrate the scope of the subject as applied to the treatment of analytical data. There is a danger that this approach may overlook some basic concepts of the subject and the reader is strongly advised to become more fully conversant with these statistical methods by obtaining a selection of the excellent texts now available. 

Bricogne. G. (1997) The Bayesian statistical viewpoint on structure determination basic concepts and examples, In Macromolecular Crystallography, Vol. 276 of Methods in Enzymology, Carter Jr., C.W. and Sweet, R.M. (Eds.), Academic Press, pp. 361 123. 

Flow cytometry Data Analysis Basic Concepts and Statistics J.V. Watson, Editor (Cambridge University... 

The QET is not the only theory in the field indeed, several apparently competitive statistical theories to describe the rate constant of a unimolecular reaction have been formulated. [10,14] Unfortunately, none of these theories has been able to quantitatively describe all reactions of a given ion. Nonetheless, QET is well established and even the simplified form allows sufficient insight into the behavior of isolated ions. Thus, we start out the chapter from the basic assumptions of QET. Following this trail will lead us from the neutral molecule to ions, and over transition states and reaction rates to fragmentation products and thus, through the basic concepts and definitions of gas phase ion chemistry. 

Although, like statistics, the details of pharmacokinetic analysis are best left to the experts, a pharmaceutical physician who is familiar with the basic concepts of how pharmacokinetic information contributes to a dossier will be able to interact more effectively with company colleagues and regulatory authority staff, it is the aim of this chapter to provide such a preliminary grounding. 

The basic concept of microdosimetry is the microdosimetric event (or, simply, event), which is energy deposition by a charged particle and its statistically correlated particles (e.g., secondary electrons from the same particle track) [15-17]. Events are important because they are statistically independent entities. The principal microdosimetric quantity, specific energy z, is defined as follows ... 

While the least squares estimator appeared several centuries ago as an independent method giving good results under certain assumptions, we have to dig deeper into mathematical statistics to see its roots, and, in particular, its limitations. This general subject is the maximum likelihood principle, one of the basic concepts of mathematical statistics. The principle is simple ... 

We will delay a more detailed discussion of ensemble thermodynamics until Chapter 10 indeed, in this chapter we will make use of ensembles designed to render the operative equations as transparent as possible without much discussion of extensions to other ensembles. The point to be re-emphasized here is that the vast majority of experimental techniques measure molecular properties as averages - either time averages or ensemble averages or, most typically, both. Thus, we seek computational techniques capable of accurately reproducing these aspects of molecular behavior. In this chapter, we will consider Monte Carlo (MC) and molecular dynamics (MD) techniques for the simulation of real systems. Prior to discussing the details of computational algorithms, however, we need to briefly review some basic concepts from statistical mechanics. 

Robust Statistics - How not to Reject Outliers - Part 1 Basic Concepts , Analyst Cambridge, 1989, 114, 1693. 

Chapter 1 deals with classical non-stoichiometric compounds. By classical, the author means that the basic concept of the phase stability has been well established from a thermodynamical point of view, and does not mean that research in this field has been fully completed. In these compounds the origin of non-stoichiometry is point defects . In the first half of the chapter, the fundamental relation between point defects and non-stoichiometry is described in detail, based on (statistical) thermodynamics, and in the second half various examples, referred to the original papers, are shown. 

Watson JV (1992). Flow Cytometry Data Analysis Basic Concepts and Statistics. Cambridge University Press, Cambridge. A detailed look at the ways we can (or should) analyze data—after we leave the flow cytometer. 

We see from this discussion that a third generalization is necessary. Up to this point in the text we have been concerned solely with the macroscopic properties. However, in order to obtain an understanding of the third law we must use some concepts concerning the entropy function, based on statistical mechanics. We do so in this chapter with the assumption that the basic concepts that are used are familiar to the reader. 

We have tried, without being overly formalistic, to develop the subject in a systematic manner with attention to basic concepts and clarity of derivations. The reader is assumed to be familiar with the basic concepts of classical mechanics, quantum mechanics, and chemical kinetics. In addition, some knowledge of statistical mechanics is required and, since not all potential readers may have that, we have included an appendix that summarizes the most important results of relevance. The book is reasonably self-contained such that a standard background in mathematics, physics, and physical chemistry should be sufficient and make it possible for the students to follow and understand the derivations and developments in the book. A few sections may be a little more demanding, in particular some of the sections on quantum dynamics and stochastic dynamics. 

This chapter introduces basic concepts in statistical analysis that are of relevance to describing and analyzing the data that are collected in clinical trials, the hallmark of new drug development. (Statistical analysis in nonclinical studies was addressed earlier in Chapter 4.) This chapter therefore sets the scene for more detailed discussion of the determination of statistical significance via the process of hypothesis testing in Chapter 7, evaluation of clinical significance via the calculation of confidence intervals in Chapter 8, and discussions of adaptive designs and of noninferiority/equivalence trials in Chapter 11. 

STATISTICAL ADJUSTMENT OF DATA, W. Edwards Deming. Introduction to basic concepts of statistics, curve fitting, least squares solution, conditions without parameter, conditions containing parameters. 26 exercises worked out. 271pp. 5X x 8h. 64685-8 Pa. 7.95... 

Analytical methods committee, Robust statistics - how not to reject outliers. Part 1. Basic concepts, Analyst, 114 (1989), 1693-1697. 

Statistical Mechanical Background. We will present a brief review of the basic statistical mechanical concepts needed in this experiment, because standard textbooks in physical chemistry vary widely in their approach. 

Our foremost goal here is to establish enough notation and a few pivotal relations that the following portions of the book can be understood straightforwardly. The following sections identify some basic thermodynamics and statistical thermodynamics concepts that will be used later. Many textbooks on thermodynamics and statistical mechanics are available to treat the basic results of this chapter in more detail students particularly interested in solutions might consult Rowlinson and Swinton (1982). 

In this book, we try to present the basic concepts in order to understand the mechanical and electrical failures of solid materials containing inherent defects or disorders. Our emphasis has been on the question why , rather than on the question when , and we concentrate mainly on the statistical aspects of their failure strength distribution. 

Static submergence, definition of 685 Statistical analysis in design basic concepts of 741-746... 

Throughout, emphasis has been placed on the logical structure of the theory and on the need to correlate every analysis with experimental operating conditions and constraints. This is coupled with an attempt to remove the mystery that seems so often to surround the basic concepts in thermodynamics. Repeatedly, the attention of the reader is directed to the tremendous power inherent in the systematic development of the subject matter. Only the classical aspects of the problem are taken up no attempt has been made to introduce the statistical approach, since the subject matter of classical thermodynamics is self-consistent and complete, and rests on an independent basis. 

Some basic concepts and definitions of statistics, chemometrics, algebra, graph theory, similarity/diversity, which are fundamental tools in the development and application of molecular descriptors, are also presented in the Handbook in some detail. More attention has been paid to information content, multivariate correlation, model complexity, variable selection, and parameters for model quality estimation, as these are the characteristic components of modern QSAR/QSPR modelling. 

To convey the basic concepts and methods of quantum mechanics that describe the discrete energy levels and the statistical behavior of microscopic systems... 

Near-IR spectroscopic tomography is discussed in a paper by Tosteson et al. [156], They extend basic concepts of statistical hypothesis testing and confidence intervals to images generated by this new procedure as used for breast cancer diagnosis. 

Devillers J. Statistical analyses in drug design and environmental chemistry Basic concepts. In Coccini T, Giannoni L, Karcher W, Manzo L and R. Roi R, editors, Quantitative structure/activity relationships (QSAR) in toxicology. JRC-Ispra CEC, 1992. p. 27-41. 

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