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2019, 01 январь (January)

DOI: 10.14489/hb.supp.2019.01.pp.001-020

Горленко О. А., Борбаць Н. М.
КОВАРИАЦИОННЫЙ АНАЛИЗ
(с. 1-20)

Аннотация. При проведении различного рода экспериментов по исследованию взаимосвязи между некоторой зависимой переменной (откликом) и одной или несколькими категориальными независимыми переменными (факторами) встречаются ситуации, когда отклик также может зависеть от еще одной или нескольких переменных, которые не могут управляться экспериментатором, но могут наблюдаться вместе с зависимой переменной. В этом случае для повышения точности эксперимента применяется специальный вид статистического анализа – ковариационный анализ.

Ключевые слова: ковариационный анализ; однофакторный эксперимент; двухфакторный эксперимент; проверка гипотез.

 

Gorlenko O. A., Borbatc N. M.
ANALYSIS OF COVARIANCE
(pp. 1-20)

Abstract. In carrying out various experiments to investigate the relationship between a certain dependent variable (response) and one or more categorical independent variables (factors), there are situations where the response may also depend on one or more variables that can not be controlled by the experimenter, but can be observed together with a dependent variable. In this case, to increase the accuracy of the experiment, a special type of statistical analysis is used – covariance analysis.

Keywords: Covariance analysis; One-factor experiment; Two-factor experiment; Hypothesis testing.

Рус

О. А. Горленко, Н. М. Борбаць (Брянский государственный технический университет, Брянск, Россия) E-mail: Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра.  

Eng

O. A. Gorlenko, N. M. Borbatc (Bryansk State Technical University, Bryansk, Russia) E-mail: Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра.  

Рус

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Eng

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4. William G. Cochran. (1957). Analysis of Covariance: Its Nature and Uses. Biometrics. Special Issue on the Analysis of Covariance, 13(3), pp. 261-281.
5. H. Fairfield Smith. (1957). Interpretation of Adjusted Treatment Means and Regressions in Analysis of Covariance. Biometrics. Special Issue on the Analysis of Covariance, 13(3), pp. 282-308.
6. Ronald D. Snee. (1971). A Note on the Use of Residuals for Examining the Assumptions of Covariance Analysis. Technometrics, 13(2), pp. 430-437.
7. James S. Degracie and Wayne A. Fuller. (1972). Estimation of the Slope and Analysis of Covariance When the Concomitant Variable is Measured with Error. Journal of the American Statistical Association, Vol. 67, 340, pp. 930-937.
8. Atiquallah M. (1964). The Robustness of the Covariance Analysis of a One-way Classification. Biometrika, 51(3–4), pp. 365-372.
9. Finney D. J. (1957). Stratification, Balance, and Covariance. Biometrics. Special Issue on the Analysis of Covariance, 13(3), pp. 373-386.
10. Hazel L. N. (1946). The Covariance Analysis of Multiple Classification Tables with Unequal Subclass Numbers. Biometrics Bulletin, Vol. 2, (2), pp. 21-25.
11. Irma Coons. (1957). The Analysis of Covariance as a Missing Plot Technique. Biometrics. Special Issue on the Analysis of Covariance, 13(3), pp. 387-405.
12. Wilkinson G. N. (1957). The Analysis of Covariance with Incomplete Data. Biometrics. Special Issue on the Analysis of Covariance, 13(3), pp. 363-372.
13. Walter T. Federer. (1957). Variance and Covariance Analyses for Unbalanced Classifications. Biometrics. Special Issue on the Analysis of Covariance, 13(3), pp. 333-362.
14. Zelen M. (1957). The Analysis of Covariance for Incomplete Block Designs. Biometrics. Special Issue on the Analysis of Covariance, 13(3), pp. 309-332.
15. Jeanne T. Truitt and H. Fairfield Smith. (1956). Adjustment by Covariance and Consequent Tests of Significance in Split-Plot Experiments. Biometrics, 12(1), pp. 23-39.
16. Acheson J. Duncan. (1959). Quality Control and Industrial Statistics. Revised Edition,. Richard D. Irwin, INC Homewood, Illinois.
17. Bradley E. Huitema. (2011). The Analysis of Covariance and Alternatives: Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies. John Wiley & Sons, Inc., Hoboken, New Jersey.
18. Ostle B. (1963). Statistics in Research: Basic Concepts and Techniques for Research Workers. The Iowa State University Press.
19. Georg A. Milliken and Dallas E. Johnson. (2002). Analysis of Messy Data. Volume III: Analysis of Covariance. Chapman&Hall/CRC.
20. Walter T. Federer. (1963). Experimental Design: Theory and Application. Second Printing. The Macmillan Company, New York.
21. George W. Snedecor. (1967). Statistical Methods: Applied to Experiments in Agriculture and Biology. Indian Edition, Allied Pacific Private Limited, Bombay.
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23. R. Lyman Ott and Michael Longnecker. (2015). An Introduction to Statistical Methods and Data Analysis. Seventh Edition,Cengage Learning, Boston.
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Рус

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