Sg/Wkbk-Cost Accounting

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* A proven best-seller: over 100,000 copies sold!

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How to Pass Computer Selection Tests
Sanjay Modha
Manufacturer: Kogan Page
ProductGroup: Book
Binding: Paperback

General | Psychology & Counseling | Health, Mind & Body | Subjects | Books

Testing & Measurement | Psychology & Counseling | Health, Mind & Body | Subjects | Books

How to Pass Secondary School Selection Tests (How to Pass)

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How to Pass Secondary School Selection Tests (How to Pass)
Mike Bryon
Manufacturer: Kogan Page Ltd
ProductGroup: Book
Binding: Paperback

Careers | People & Places | Children's Books | Subjects | Books

General | Ages 9-12 | Children's Books | Subjects | Books

Testing | Education | Reference | Subjects | Books

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HOW TO PASS TECHNICAL SELECTION TESTS
MIKE BRYON
Manufacturer: KOGAN
ProductGroup: Book
Binding: Paperback
ASIN: B000S99MX4

Book Description

Growing Up with Epilepsy provides parents with the tools needed to raise a child with epilepsy, to support his/her social development, provide effective discipline, and negotiate the educational system.

Customer Reviews:

An important tool for everyday living.......2003-09-14

Parents who must deal with the daily unpredictability of seizures and the side effects of medication often find it confusing to understand what to expect. Growing Up With Epilepsy will appeal to busy parents who want a quick reference guide: information is organized in a manner easy to look up, chapters discuss social and behavioral as well as psychological concerns and issues, and parents receive basic tools to help their kids through all manner of concerns. An important tool for everyday living.

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Epilepsy: A Practical Guide to Coping
Ley Sander , and Pam Thompson
Manufacturer: Crowood Pr
ProductGroup: Book
Binding: Paperback

General | Self-Help | Health, Mind & Body | Subjects | Books

General | Medicine | Subjects | Books

General | Medical | Professional & Technical | Subjects | Books
ASIN: 1852231785

LIVING WITH EPILEPSY: A PRACTICAL GUIDE TO THE CAUSES AND TREATMENTS

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LIVING WITH EPILEPSY: A PRACTICAL GUIDE TO THE CAUSES AND TREATMENTS
SUE USISKIN DAVID CHADWICK
Manufacturer: VERMILION
ProductGroup: Book
Binding: Paperback

General | Self-Help | Health, Mind & Body | Subjects | Books

General | Health, Mind & Body | Subjects | Books

Product Description

Nearly all the information we know about the Universe comes from the study of light as it reaches us. The understanding of this information contained in light requires both telescopes capable of resolving light into its different component colors, as well as detailed knowledge of the quantum mechanical behavior of atoms and molecules. This unique book, which is based on a third-year undergraduate course given by the author at University College London, presents the basic atomic and molecular physics necessary to understand and interpret astronomical spectra. It explains what information can be extracted from these spectra and how. Extensive use is made of contemporary astronomical spectral data to both motivate the study of the underlying atomic physics and to illustrate the results.

Customer Reviews:

Practical next step.......2007-06-16

I have a BSci in Astronomy and have not yet attended grad school. I work for a world class observatory that uses spectroscopy of some sort in almost all of the science we do. Having only had brief overviews as an undergrad, this book was a perfect next step allowing me to gain a more thorough understanding the science that I am part of. Some prior knowledge of atomic physics is very helpful.
The problems at the end of the chapters are useful to verify understanding of the material.

A good introduction.......2006-08-07

This is a good introduction to the topic but its a little thin weighing in at a little less than 200 pages. The book is very compact and written at the college level. It stresses the connection between spectra and quantum mechanics [of course]. The book would make a good college or graduate level textbook as a course in itself or an adjunct to physics or quantum mechanics.

The Table of Contents:
1. Why record spectra of Astronomical Objects
2. The nature of Spectra
3. Atomic Hydrogen
4. Complex Atoms
5. Helium Spectra
6. Alkali Atoms
7. Spectra of Nebulea
8. X-ray Spectra
9. Molecular Spectra
10. Solutions to Problems
11. Bibliography

Third Year Undergrad level........2005-11-02

It comes as a surprise to most people when they learn that rarely does a professional astronomer actually look through a telescope. Most of the time, in fact, he isn't interested in the appearance at all. What he actually wants (usually) is a spectroscopic analysis of the light coming from the object being observed.

The biggest telescope cannor resolve a star into anything but a point of light. The information contained in that point of light can tell you a lot about that star. The composition of its atmosphere, its motion, its temperature and more can all be determined by analyzing the light beam.

This book was developed for a third year undergraduate level course. It presumes that the student had a prior course in Quantum Mechanics which covered the Hydrogen Atom, but no further atomic physics or spectroscopy.

Introduction to Advanced Astrophysics (Geophysics and Astrophysics Monographs)

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Introduction to Advanced Astrophysics (Geophysics and Astrophysics Monographs)
V. Kourganoff
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

Astronomy | Astronomy | Science | Subjects | Books

Astrophysics & Space Science | Astronomy | Science | Subjects | Books

Solar System | Astronomy | Science | Subjects | Books

French | Foreign Language Nonfiction | Nonfiction | Subjects | Books

Nonfiction | French | Foreign Language Books | Specialty Stores | Books

Professional & Technical | French | Foreign Language Books | Specialty Stores | Books

All French Books | French | Foreign Language Books | Specialty Stores | Books
ASIN: 9027710023

Space Physics: An Introduction to Plasmas and Particles in the Heliosphere and Magnetospheres (Advanced Texts in Physics : Physics and Astronomy Online Library)

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Space Physics: An Introduction to Plasmas and Particles in the Heliosphere and Magnetospheres (Advanced Texts in Physics : Physics and Astronomy Online Library)
May-Britt Kallenrode
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

Astronomy | Astronomy | Science | Subjects | Books

Astrophysics & Space Science | Astronomy | Science | Subjects | Books

Solar System | Astronomy | Science | Subjects | Books

General | Science | Subjects | Books

General | Physics | Science | Subjects | Books

Physics of the Solar Corona: An Introduction with Problems and Solutions (Springer Praxis Books / Astronomy and Planetary Sciences)
Plasma Physics for Astrophysics (Princeton Series in Astrophysics)
Introduction to Space Physics (Cambridge Atmospheric & Space Science)

ASIN: 3540412492

Book Description

The phenomena of space physics are complex and their understanding often requires the integration of different concepts. To help the beginner, this book uses a new methodological approach. The first chapters introduce simple concepts of plasma physics and describe where these can be applied in space physics. Subsequent chapters are devoted to more complex observations, interpreted in terms of the concepts introduced earlier. New, more difficult, concepts are introduced as they are required. Thus observations and physical concepts are interwoven to give basic explanations of phenomena and also show the limitations in these explanations and identify some fundamental questions. This second edition has been updated and extended. Improvements include: the use of SI units; addition of recent results from SOHO and Ulysses; improved treatment of the magnetosphere as a dynamic phenomenon; text restructured to provide a closer coupling between basic physical concepts and observed complex phenomena.

Advanced physiography (physiographic astronomy) designed to meet the requirements of students preparing for the elementary and advanced stages of physiography ... and as an introduction to physical astronomy

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Advanced physiography (physiographic astronomy) designed to meet the requirements of students preparing for the elementary and advanced stages of physiography ... and as an introduction to physical astronomy
John Mills
Manufacturer: Chapman and Hall
ProductGroup: Book
Binding: Unknown Binding
ASIN: B0008C42JA

Book Description

Make the most of your data!
This new title will serve both as an introduction and as a practical guide to those techniques of chemometrics which are applicable to environmental analysis. By describing the optimum methods of data analysis it will help all chemists in this field to save time and money.
Because the authors demonstrate the most important chemometric methods with the aid of numerous examples, the reader will learn to solve a given problem by use of the appropriate method. Applications range from sampling, through laboratory analysis, to evaluation. Interpretation of the findings is explained clearly. The text covers not only basic methods such as univariate statistics, regression analysis, and static test planning, but also multivariate data analysis, for example, cluster analysis, principal components analysis, and factor and discriminant analysis. Case studies show the enormous possibilities, and the limits, of chemometric methods.
The book will help all environmental analytical chemists, even those with only a basic knowledge of mathematics, to optimize the evaluation and interpretation of the results of their measurements.

Chemometric interpretation of pesticide occurence in soil samples from an intensive horticulture area in north Portugal [An article from: Analytica Chimica Acta]

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Chemometric interpretation of pesticide occurence in soil samples from an intensive horticulture area in north Portugal [An article from: Analytica Chimica Acta]
C. Goncalves , J.C.G. Esteves da Silva , and Alpendurada
Manufacturer: Elsevier
ProductGroup: Book
Binding: Digital

Elsevier | By Publisher | e-Docs | Formats | Books
ASIN: B000RR71GC

Book Description

This digital document is a journal article from Analytica Chimica Acta, published by Elsevier in . The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
An extensive monitoring programme of pesticides was carried out in soil samples from an intensive horticulture area in north of Portugal, putting into practice the needs for increased control of soil quality as far as organic pollution is concerned. The area under investigation was additionally defined as vulnerable to nitrates due to local soil and aquifer characteristics, which might be extended to pesticides contamination. Five sampling sites were selected and soils analysed at three depths in eight sampling campaigns, for the period of 2 years. A stepwise multivariate statistical approach was selected to uncover most relevant patterns inside a complex environmental data matrix. Cluster analysis was applied both to group pesticides and samples, giving a primary and unsupervised overlook of privileged relationships. Clusters of persistent pesticides and selected herbicides were identified, whereas sample classes were also formed and disposed geographically. Thirty eight percent of analysed soils samples fell into one class characterized by low contamination (class 1 in cluster analysis), which is entirely representative of the sampling site no. 1. Afterwards, linear discriminant analysis was applied to identify those pesticides, which had a higher impact in the definition of classes. Finally, factor analysis using a five component model was implemented in order to bring to light the constitution and data variance explained by each of the five main principal components, as well as, their relation to pest management practices. A factor was identified (PC1 - 22% variance) composed of chlorinated pesticides, which was representative of one of the investigated sites indicating its high contamination status. Qualitative main findings and class average concentration values were obtained through this multivariate statistical approach.

Chemometrics methods for the investigation of methylmercury and total mercury contamination in mollusks samples collected from coastal sites along the ... [An article from: Environmental Pollution]

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Chemometrics methods for the investigation of methylmercury and total mercury contamination in mollusks samples collected from coastal sites along the ... [An article from: Environmental Pollution]
W. Yawei , L. Lina , S. Jianbo , and J. Guibin
Manufacturer: Elsevier
ProductGroup: Book
Binding: Digital

Elsevier | By Publisher | e-Docs | Formats | Books
ASIN: B000RR3VFW

Book Description

This digital document is a journal article from Environmental Pollution, published by Elsevier in 2005. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
The development and application of chemometrics methods, principal component analysis (PCA), cluster analysis and correlation analysis for the determination of methylmercury (MeHg) and total mecury (HgT) in gastropod and bivalve species collected from eight coastal sites along the Chinese Bohai Sea are described. HgT is directly determined by atomic fluorescence spectrometry (AFS), while MeHg is measured by a laboratory established high performance liquid chromatography-atomic fluorescence spectrometry system (HPLC-AFS). One-way ANOVA and cluster analysis indicated that the bioaccumulation of Rap to accumulate Hg was significantly (P <0.05) different from other mollusks. Correlation analysis shows that there is linear relationship between MeHg and HgT in mollusks samples collected from coastal sites along the Chinese Bohai Sea, while in mollusks samples collected from Hongqiao market in Beijing City, there is not any linear relationship.

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Chemometrics in Environmental Analysis.
Jurgen W. Einax
Manufacturer: see notes for publisher info
ProductGroup: Book
Binding: Hardcover
ASIN: B000M49U78

Book Description

Optimal Data Analysis: A Guidebook With Software for Windows is a powerful new system for examining information and making predictions. Optimal data analysis (ODA) identifies a statistical model that yields the theoretical maximum possible level of predictive accuracy. Here is the first and only comprehensive exposition of the ODA paradigm and the first and only statistical software for conducting ODA analyses.

This powerful system is self-contained, stands alone, and provides users who have never heard of the ODA paradigm with all of the tools required to conduct analyses quickly and with a minimum of effort. The methodological infrastructure is explained conceptually, without requiring equations. A cornucopia of easy-to-understand examples—that alternative statistical packages fail to solve—are provided and illustrate how to conduct ODA in various contexts such as

- psychology,
- medicine,
- finance,
- biology,
- political science,
- geology,
- engineering, and
- sports.

The book discusses predictive analysis step-by-step using the ODA method, from defining the prediction goal and potential predictor variables, through evaluating model classification performance, statistical significance, and validity findings. Every example illustrates how to use the ODA software, and how to interpret and describe the program output.

This statistical software system will prove its usefulness and flexibility for researchers, practitioners, and analysts in all quantitative fields, and will become a new standard in predictive analysis.

Customer Reviews:

Useful way to Analyze Quanities of Data.......2005-02-08

Optimal Data Analysis: A Guidebook with Software for Windows, CD-Rom Edition by Paul R. Yarnold, Robert C. Soltyslk (American Psychological Association) Optimal Data Analysis: A Guidebook With Software for Windows offers the only statistical analysis paradigm that maximizes (weighted) predictive accuracy. This unique book fully explains this paradigm and includes simple-to-use software that empowers a universe of associated analyses. For any specific sample and exploratory or confirmatory hypothesis, optimal data analysis (ODA) identifies the statistical model that yields maximum predictive accuracy, assesses the exact Type I error rate, and evaluates potential cross-generalizability.
No other software can accomplish analyses possible via ODA. The accompanying software offers the following features, among others:
* Optimal analogues of traditional statistical procedures such as t-test, chi square, Markov analysis, inter-rater reliability analysis, time-series analysis, single-case analysis, and tine-tuning of traditional multivariable models such as logistic regression analysis or discriminant analysis; multiple sample analysis to circumvent Simpson's paradox;
* cross-generalizability (hold-out) or leave-one-out (jackknife) validity analysis;
* weighting by prior odds, cost or return, and one- or two-tailed hypothesis testing for any analysis; multidimensional analysis of structure underlying bias in data;
* sequentially rejective Bonferroni-type multiple comparisons procedures;
* a priori alpha splitting;
* hierarchically optimal classification tree analysis.
The book provides intuitive examples drawn from disciplines such as psychology, medicine, biology, political science, accounting, economics, education, statistics, finance, psychiatry, biochemistry, public health, geology, and sports. This theoretical approach and statistical software package will prove its usefulness and flexibility for researchers, practitioners and analysts in all quantitative fields, and will become the new standard for accuracy of models derived in statistical analysis.
DA-pronounced with a long "O" sound ("oh-dah")-is the short way of referring
to the "optimal data analysis" paradigm. This new statistical paradigm is simple to learn, the software is easy to operate, and the findings of ODA analyses have intuitive interpretations. Nonetheless, the paradigm and the software are powerful and rich. This book describes the ODA paradigm and software and demonstrates how to apply ODA in the analysis of data. Everything needed to understand ODA is contained within this book, and all ODA analyses within this book can be accomplished using the accompanying software. Only moments away from jumping directly into the fray, we pause briefly to address four questions frequently asked by beginner and expert alike as they ponder the merits of learn¬ing ODA.
ODA is a new statistical paradigm-a quantitative scientific revolution, so to speak. Perhaps the best way to illustrate what this means is by example.
The ordinary least squares (OLS) paradigm maximizes a variance ratio for a given sample, and includes analyses such as t test, correlation, multiple regression analysis, and multivariate analysis of variance. If one wishes to maximize a variance ratio, then the OLS paradigm is required, obviously, because that is what it does. That is, maximizing variance ratios is what the "formulas" that compute t, F, and r actually accomplish for a given sample.
In contrast, the maximum likelihood (ML) paradigm maximizes the value of the likelihood function for a given sample. This paradigm includes analyses such as chi-square, logistic regression analysis, log-linear analysis, and structural equation modeling. If one wishes to maximize the value of the likelihood function, then the ML paradigm is required.
In contrast, ODA maximizes the accuracy of a model. As a simple example, imagine we wished to assess whether two groups-Group A and Group B-of independent observations can be discriminated on the basis of their score on a test. ODA identifies the model that uses the test score in a manner such that it discriminates members of A versus B with theoretical maximum possible accuracy. To understand how this is accomplished, recall that the model-any model, every model-can actually physically be used to compute each observation's "score" via an equation or "formula." The resulting score is then considered with respect to the decision criteria of the particular procedure and a prediction is then made on the basis of the model. In the present example, in some instances the model (regardless of the methodology by which it was developed) will predict that an observation is from Group A. Other observations will be predicted to be from Group B. Every time the predicted group membership status of an observation is correct-the same as the actual group member-ship status, a point is scored. An incorrect prediction scores no points. Obviously, the largest number of points that it is possible to attain for a sample of N observations, in theory, is equal to N, the number of observations in Groups A and B that are classified by the model. Clearly, this maximum score is only possible if all observations are correctly predicted to be from A or B by the model. The minimum score possible is obviously zero points, in which case all observations are incorrectly predicted to be from A or B by the model.
By definition, an ODA model achieves maximum possible accuracy for a given sample of data, in the sense that no other model that is based on the test score can achieve a superior number of points. All possible alternative models are (explicitly or implicitly) evaluated to literally prove this, which is one reason why ODA is "computationally intensive." As OLS maximizes a variance ratio for a given sample of data, and as ML maximizes the value of the likelihood function for a given sample of data, ODA maximizes the accuracy of the model for a given sample of data. Of course, if different observations can be weighted by a different number of points, for example if a "natural" weighting metric, such as time, weight, or cost is available, then weighted accuracy may be maximized (or cost minimized), as may be desired by the operator.
Every type of analysis (i.e., every specific configuration of data, constraints, and hypotheses) that can be conducted in the OLS and ML paradigms can be conducted in the ODA paradigm. The ODA paradigm can conduct many analyses that one simply cannot do using either OLS or ML paradigms. ODA is much more general, and much more encompassing of different data, constraints, and hypothesis configurations, than are the alternative statistical paradigms. The ODA paradigm is, quite literally, "new and improved." Using this paradigm, and only using this paradigm, is one able to identify maximally accurate models for a given sample.
The ODA paradigm is vastly superior to alternative paradigms. Consider first, conceptual clarity. For every problem analyzed via ODA there is one precise, optimal analysis-a specific given data configuration and hypothesis dictates the exact nature of the ODA model that is appropriate. Using traditional statistics, in most applications several different analyses are feasible-all reflecting some degree of lack of fit between their required underlying distribu¬tional assumptions and the actual character of the data. Consider second, ease of interpretation. Every ODA analysis provides the same intuitive goodness-of-fit index: for every ODA analysis an index is computed on which 0 reflects the accuracy expected by chance for the sample, and 100 reflects perfect accuracy. Using traditional statistics, different analyses provide different goodness-of-fit indices that are non-intuitive and that are not directly comparable across procedures. Consider third, maximum accuracy. Every ODA analysis provides a model that guarantees maximum possible accuracy. Using traditional statistics, no analysis provides a model that explicitly guarantees maximum possible accuracy. Consider fourth, valid Type I error. No ODA analysis requires any simplifying assumptions, and p is always valid and accurate-a permutation probability derived via Fisher's randomization method, invariant over any monotonic (i.e., transformed values either always increase or always decrease) transformation of the data. Traditional analyses require simplifying assumptions (e.g., normal¬ity), p is only valid if the required assumptions are true for one's data, and p may be inconsistent over transformations of the data.
An obvious advantage of ODA software is availability (the first and currently the only software available that performs ODA). There are many good packages available for performing OLS and/or ML analysis, and many are an order of magnitude more expensive than the ODA book/software. Comparing software across paradigms, the ODA software is superior to software of earlier paradigms for two important reasons. Consider first, ease of learning and teaching. Everything needed to understand the ODA paradigm and analyze data is discussed in this book. Many courses, books, and articles are needed to understand traditional statistics and to correctly operate associated software, requiring years of study. Consider second, ease of use. Most types of ODA analyses require the same basic set of seven programming commands. Using traditional procedures requires learning of numerous-hundreds-system unique programming commands.

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