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Multivariate Statistical Analysis
Psychophysiology, 1973ABSTRACTGeneral multivariate statistical theory and three statistical models (multi‐variate analysis of variance, canonical correlation analysis, and factor analysis) are described. Numerical examples, mathematical notes, an annotated bibliography, and references to computer programs are presented.
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IEEE Design & Test of Computers, 1985
Statistical Fault Analysis, or Stafan, is proposed as an alternative to fault simulation of digital circuits. This method defines Controllabilities and observabilities of circuit nodes as probabilities estimated from signal statistics of fault-free simulation. Special Procedures deal with these quantities at fanout and feedback nodes.
Sunil K. Jain, Vishwani D. Agrawal
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Statistical Fault Analysis, or Stafan, is proposed as an alternative to fault simulation of digital circuits. This method defines Controllabilities and observabilities of circuit nodes as probabilities estimated from signal statistics of fault-free simulation. Special Procedures deal with these quantities at fanout and feedback nodes.
Sunil K. Jain, Vishwani D. Agrawal
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A statistical analysis of luck
Synthese, 2018A modal analysis of luck, due to Duncan Pritchard, has become quite popular in recent years. There are many reasons to like Pritchard’s analysis, but at least two compelling problems have been identified. So I propose an alternative analysis of luck based on the laws of statistical mechanics.
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Statistical Analysis Simplified
Technometrics, 2000Statistical Analysis Simplijed is the introductory volume in the H. James Harrington Performance Improvement Series published by McGraw-Hill. The three authors have almost a century of business and quality experience between them. They have produced a highly readable explanation of statistical thinking and the seven traditional quality-control tools ...
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Technometrics, 2000
Preface Notation 1. Fundamental Concepts 2. Examples of Probability Functions 3. The Monte Carlo Method 4. Statistical Tests 5. General Concepts of Parameter Estimation 6. The Method of Maximum Likelihood 7. The Method of Least Squares 8. The Method of Moments 9. Statistical Errors, Confidence Intervals and Limits 10.
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Preface Notation 1. Fundamental Concepts 2. Examples of Probability Functions 3. The Monte Carlo Method 4. Statistical Tests 5. General Concepts of Parameter Estimation 6. The Method of Maximum Likelihood 7. The Method of Least Squares 8. The Method of Moments 9. Statistical Errors, Confidence Intervals and Limits 10.
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Current Protocols Essential Laboratory Techniques, 2008
AbstractIn this appendix, we provide an outline of methods used in analyzing biological data. We give a summary of types of data encountered and the appropriate methods to apply for the questions of interest. Statistical techniques described include the t test, the Wilcoxon rank sum test, the Mann‐Whitney‐Wilcoxon test, ANOVA, regression, and the chi ...
John Kloke, Johanna Hardin
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AbstractIn this appendix, we provide an outline of methods used in analyzing biological data. We give a summary of types of data encountered and the appropriate methods to apply for the questions of interest. Statistical techniques described include the t test, the Wilcoxon rank sum test, the Mann‐Whitney‐Wilcoxon test, ANOVA, regression, and the chi ...
John Kloke, Johanna Hardin
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The statistical analysis of kappa statistics in multiple samples
Journal of Clinical Epidemiology, 1996Methods are presented for assessing and comparing the results of k > or = 2 independent samples of measured agreement or concordance, where in each sample a given member of a pair of observations is classified according to the presence or absence of a binary trait.
A, Donner, N, Klar
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Statistical Analysis of Multilocus Recombination
Biometrics, 1983A general formula for the frequency of different recombinant gamete types, in terms of the underlying distribution of crossovers, is derived. This formula may be applied to any theoretical model of recombination in which it is assumed that there is no chromatid interference.
Risch, N., Lange, K.
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2005
Deoxyribonucleic acid (DNA) profiling has become a very powerful method for forensic human identification, and statistics plays an important role in assessing the uncertainty in identification and evaluating the weight of DNA evidence. Statistical calculation of match probabilities for various single-source problems, paternity index for differentiating
Hu, YQ, Fung, TWK
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Deoxyribonucleic acid (DNA) profiling has become a very powerful method for forensic human identification, and statistics plays an important role in assessing the uncertainty in identification and evaluating the weight of DNA evidence. Statistical calculation of match probabilities for various single-source problems, paternity index for differentiating
Hu, YQ, Fung, TWK
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Statistical Analysis of Introgression
Biometrics, 1966SUMMARY Measurements of introgression may be made on scales established by principal components, canonical correlation vectors, discriminant functions, hybrid indices, and a proposed distance analysis. The distance analysis developed is the most sensitive scale used.
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