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Penn / Berridge

Statistical Analysis of Continuous Data

Medium: Buch
ISBN: 978-1-4462-4869-0
Verlag: Sage Publications
Erscheinungstermin: 18.07.2013
Lieferfrist: bis zu 10 Tage

This new four-volume collection tracks the development of statistical methods for continuous, or interval-scale data. Examples of such data occurring in the social sciences include indicators of educational attainment (for example, GCSE scores) and psychometric measures of intelligence. Framed by a new contextualising introduction, the volumes are organised thematically, covering key areas to enable a well-rounded and comprehensive understanding of the discipline:

Volume One: Statistical Foundations for the Analysis of Continuous Data
Volume Two: Basic Principles for the Statistical Modelling of Continuous Data
Volume Three: Multivariate Analyses of Continuous Data
Volume Four: Statistical Modelling of Multivariate Continuous Data


Produkteigenschaften


  • Artikelnummer: 9781446248690
  • Medium: Buch
  • ISBN: 978-1-4462-4869-0
  • Verlag: Sage Publications
  • Erscheinungstermin: 18.07.2013
  • Sprache(n): Englisch
  • Auflage: Four-Volume Set Auflage
  • Serie: SAGE Benchmarks in Social Research Methods
  • Produktform: Kartoniert
  • Gewicht: 3357 g
  • Seiten: 1800
  • Format (B x H x T): 175 x 249 x 127 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

Roger Penn is currently Professor of Sociology in the School of Sociology, Social Policy & Social Work at Queen’s University Belfast. Previously, he was Professor of Economic Sociology at Lancaster University. He has been a visiting professor at UCLA, UC Berkeley, and the University of Bologna and has authored 14 books including Skilled Workers in the Class Structure; Class, Power and Technology; Social Change and Economic Life in Britain; and Children of International Migrants in Europe. He has edited a range of books including Skill and Occupational Change, Trade Unions in Recession, and two 4 Volume SAGE Series: Social Statistics and The Statistical Analysis of Continuous Data. He has also authored around 150 articles in peer-reviewed journals since 1975. He is currently on the editorial board of the European Journal for Sport and Society. He has a long-standing interest in the sociology of football. He has taught courses in this field for over a decade both at Lancaster University and more recently at Queen’s University. He has published a range of articles over recent years that have examined football sociologically. These have included several SAGE Research Methods Case Studies.

VOLUME ONE: STATISTICAL FOUNDATIONS FOR THE ANALYSIS OF CONTINUOUS DATA
Methods of Statistics - F. Edgeworth

Some New Methods of Measuring Variation in General Prices - F. Edgeworth

Contributions to the Mathematical Theory of Evolution - Karl Pearson

Regression, Heredity and Panmixia

Notes on the History of Pauperism in England and Wales from 1850, Treated by the Method of Frequency-Curves, with an Introduction on the Method - G. Udny Yule

On the Theory of Correlation - G. Udny Yule

Mathematical Contributions to the Theory of Evolution - Karl Pearson

On the Reconstruction of the Stature of Prehistoric Races

Probable Error of a Mean - L. Gossett ('Student')

On the Criterion of Goodnes -of-Fit of the Regression Lines and on the Best Methods of Fitting Them to the Data - E. Slutsky

Notes on the History of Correlation - Karl Pearson
On the 'Probable Error' of a Co-Efficient of Correlation Deduced from a Small Sample - R.A. Fisher
The Goodness-of-Fit of Regression Formulae and the Distribution of Regression Co-Efficients - R.A. Fisher

Applications of 'Students' Distribution - A. Fisher

VOLUME TWO: BASIC PRINCIPLES FOR THE STATISTICAL MODELING OF CONTINUOUS DATA
Testing for Normality - R. Geary

A General Distribution Theory for a Class of Likelihood Criteria - G. Box

A Method for Judging All Contrasts in the Analysis of Variance - Henry Scheffe

An Analysis of Transformations - G. Box and D. Cox

Issues in Multiple Regression - Robert Gordon

Generalized Linear Models - J. Nelder and R. Wedderburn

Quasi-Likelihood Functions, Generalized Linear Models and the Gauss-Newton Method - R. Wedderburn

Comparison of Stopping Rules in forward 'Stepwise' Regression - Robert Bendall and A. Afifi

Additive and Multiplicative Models and Interactions - J. Darroch and T. Speed

Maximum Likelihood Estimation and Large-Sample Inference for Generalized Linear and Non-Linear Regression Models - Bent Jorgensen

Iteratively Reweighted Least Squares for Maximum Likelihood Estimation and Some Robust and Resistant Alternatives - P. Green

Selection of Subsets of Regression Variables - Alan Miller

A Fast Model Selection Procedure for Large Families of Models - D. Edwards and T. Havranek

Control of Leaf Expansion in Sunflower (Helianthus anuus L.) by Nitrogen Nutrition - S. Palmer et al

Saccadic Eye Movements in Families Multiply Affected with Schizophrenia - T Crawford et al

The Maudsley Family Study

VOLUME THREE: MULTIVARIATE ANALYSES OF CONTINUOUS DATA
The Generalization of Student's Ratio - Harold Hotelling

On the Generalized Distance in Statistics - P. Mahalanobis

Significance Test for Sphericity of a Normal n-Variate Distribution - John Mauchly

Tests with Discriminant Functions in Multivariate Analysis - Radhakrishna Rao

Sample Criteria for Testing Equality of Means, Equality of Variances and Equality of Co-Variances in a Normal Multivariate Distribution - S. Wilks

An Extension of Box's Results on the Use of the F Distribution in Multivariate Analysis - Seymour Geisser and Samuel Greenhouse
Multivariate Analysis of Variance (MANOVA) - H. Smith et al
Some Non-Central Distribution Problems in Multivariate Analysis - A. Constantine

Asymptotic Theory for a Principal Component Analysis - T. Anderson

A Generalized Multivariate Analysis of Variance Model Useful Especially for Growth Curve Problems - Richard Potthoff and S. Roy

Some Distance Properties of Latent Root and Vector Methods Used in Multivariate Analysis - J. Gower

The Analysis of Association among Many Variates - E. Williams

A General Maximum Likelihood Discriminant - N. Day and D. Kerridge

On Some Invariant Criteria for Grouping Data - H. Friedman and J. Rubin

On the Non-Central Distributions of Two Test Criteria in a Multivariate Analysis of Variance - C. Khatri and K. Pillai