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Breakthroughs in Statistics
Overview of attention for book
Table of Contents
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Book Overview
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Chapter 1
Introduction to Galton (1889) Co-Relations and Their Measurement, Chiefly from Anthropometric Data
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Chapter 2
Introduction to McKendrick (1926) Applications of Mathematics to Medical Problems
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Chapter 3
Introduction to Yates and Cochran (1938) The Analysis of Groups of Experiments
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Chapter 4
Introduction to Rao (1948) Large Sample Tests of Statistical Hypotheses Concerning Several Parameters with Applications to Problems of Estimation
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Chapter 5
Introduction to Cornfield (1951) A Method of Estimating Comparative Rates from Clinical Data. Applications to Cancer of the Lung, Breast, and Cervix
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Chapter 6
Introduction to Metropolis, Rosenbluth, Rosenbluth, Teller, and Teller (1953) Equations of State Calculations by Fast Computing Machines. J. Chem. Phys .,21, 1087–1092. and Geman and Geman (1984) Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images. IEEE Trans. Pattern Anal. Machine Intelligence ,6, 721–741.
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Chapter 7
Introduction to Whittle (1953) The Analysis of Multiple Stationary Time Series
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Chapter 8
Introduction to Daniels (1954) Saddlepoint Approximations in Statistics
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Chapter 9
Introduction to Cooley and Tukey (1965) An Algorithm for the Machine Calculation of Complex Fourier Series
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Chapter 10
Introduction to Hájek (1970) A Characterization of Limiting Distributions of Regular Estimates
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Chapter 11
Introduction to Hastings (1970) Monte Carlo Sampling Methods Using Markov Chains and Their Applications
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Chapter 12
Introduction to Lindley and Smith (1972) Bayes Estimates for the Linear Model
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Chapter 13
Introduction to Besag (1974) Spatial Interaction and the Statistical Analysis of Lattice Systems
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Chapter 14
Introduction to Levit (1974) On the Optimality of Some Statistical Estimates
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Chapter 15
Introduction to Aalen (1978) Nonparametric Inference for a Family of Counting Processes
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Chapter 16
Introduction to Morris (1982) Natural Exponential Families with Quadratic Variance Functions
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Chapter 17
Introduction to Barndorff-Nielsen (1983) On a Formula for the Distribution of the Maximum Likelihood Estimator
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Chapter 18
Introduction to Rousseeuw (1984) Least Median of Squares Regression
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Chapter 19
Introduction to Liang and Zeger (1986) Longitudinal Data Analysis Using Generalized Linear Models
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Chapter 20
Introduction to Hall (1988) Theoretical Comparison of Bootstrap Confidence Intervals
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Chapter 21
Introduction to Gelfand and Smith (1990) Sampling-Based Approaches to Calculating Marginal Densities
Overall attention for this book and its chapters
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Mentioned by
twitter
3
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syllabi
2
institutions with syllabi
wikipedia
3
Wikipedia pages
Citations
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Dimensions
Readers on
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Mendeley
Book overview
1. Introduction to Galton (1889) Co-Relations and Their Measurement, Chiefly from Anthropometric Data
2. Introduction to McKendrick (1926) Applications of Mathematics to Medical Problems
3. Introduction to Yates and Cochran (1938) The Analysis of Groups of Experiments
4. Introduction to Rao (1948) Large Sample Tests of Statistical Hypotheses Concerning Several Parameters with Applications to Problems of Estimation
5. Introduction to Cornfield (1951) A Method of Estimating Comparative Rates from Clinical Data. Applications to Cancer of the Lung, Breast, and Cervix
6. Introduction to Metropolis, Rosenbluth, Rosenbluth, Teller, and Teller (1953) Equations of State Calculations by Fast Computing Machines. J. Chem. Phys .,21, 1087–1092. and Geman and Geman (1984) Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images. IEEE Trans. Pattern Anal. Machine Intelligence ,6, 721–741.
7. Introduction to Whittle (1953) The Analysis of Multiple Stationary Time Series
8. Introduction to Daniels (1954) Saddlepoint Approximations in Statistics
9. Introduction to Cooley and Tukey (1965) An Algorithm for the Machine Calculation of Complex Fourier Series
10. Introduction to Hájek (1970) A Characterization of Limiting Distributions of Regular Estimates
11. Introduction to Hastings (1970) Monte Carlo Sampling Methods Using Markov Chains and Their Applications
12. Introduction to Lindley and Smith (1972) Bayes Estimates for the Linear Model
13. Introduction to Besag (1974) Spatial Interaction and the Statistical Analysis of Lattice Systems
14. Introduction to Levit (1974) On the Optimality of Some Statistical Estimates
15. Introduction to Aalen (1978) Nonparametric Inference for a Family of Counting Processes
16. Introduction to Morris (1982) Natural Exponential Families with Quadratic Variance Functions
17. Introduction to Barndorff-Nielsen (1983) On a Formula for the Distribution of the Maximum Likelihood Estimator
18. Introduction to Rousseeuw (1984) Least Median of Squares Regression
19. Introduction to Liang and Zeger (1986) Longitudinal Data Analysis Using Generalized Linear Models
20. Introduction to Hall (1988) Theoretical Comparison of Bootstrap Confidence Intervals
21. Introduction to Gelfand and Smith (1990) Sampling-Based Approaches to Calculating Marginal Densities
Summary
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Syllabi
Wikipedia
Dimensions citations
This data is correct as of December 2015 - for more up to date information, please visit
https://opensyllabus.org/
So far, Altmetric has seen this research output assigned in
2
syllabi from
2
institutions on Open Syllabus Project.
Institution
Syllabi count
Course subject areas covered
Montana State University
1
Unknown
University of Washington-Seattle Campus
1
Business