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Associations of heavy metal mixtures with blood pressure among U.S. adults in NHANES 2017-2018 by four statistical models. [PDF]
Chin Med J (Engl)Wu L +5 more
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Targeted Anthocyanin Enrichment of Cranberry Juice by Electrodialysis with Filtration Membranes: Impact of Filtration Membrane Physicochemical Properties and Predictive Statistical Models. [PDF]
Membranes (Basel)Revellat E, Bazinet L.
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Statistical Models in Epidemiology.
Journal of the American Statistical Association, 19955. Statistical Models in Epidemiology. By D. Clayton and M. Hills. ISBN 0 19 852221 5. Oxford University Press, Oxford, 1993. 368 pp. £30.
M. K., David Clayton, Michael Hills
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2019
In this chapter, we present statistical modelling approaches for predictive tasks in business and science. Most prominent is the ubiquitous multiple linear regression approach where coefficients are estimated using the ordinary least squares algorithm. There are many derivations and generalizations of that technique. In the form of logistic regression,
Dettling, Marcel, Ruckstuhl, Andreas
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In this chapter, we present statistical modelling approaches for predictive tasks in business and science. Most prominent is the ubiquitous multiple linear regression approach where coefficients are estimated using the ordinary least squares algorithm. There are many derivations and generalizations of that technique. In the form of logistic regression,
Dettling, Marcel, Ruckstuhl, Andreas
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2008
Statistical models provide an alternative approach to using dynamical models in seasonal climate forecasting. In statistical models relationships between one set of data, the predictors, and a second set, the predictands, are sought. Common predictands include seasonal mean temperatures and accumulated precipitation, and are typically predicted using ...
Mason, Simon J., Baddour, Omar
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Statistical models provide an alternative approach to using dynamical models in seasonal climate forecasting. In statistical models relationships between one set of data, the predictors, and a second set, the predictands, are sought. Common predictands include seasonal mean temperatures and accumulated precipitation, and are typically predicted using ...
Mason, Simon J., Baddour, Omar
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2020
This chapter describes the application of statistical concepts with illustration about statistical models, probability, normal distribution, and analysis of variance (ANOVA). Statistical analysis is an important action process in research that deals with data. It follows well-defined, systematic, and mathematical procedures and rules.
Mukhtar Ahmed, Mukhtar Ahmed
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This chapter describes the application of statistical concepts with illustration about statistical models, probability, normal distribution, and analysis of variance (ANOVA). Statistical analysis is an important action process in research that deals with data. It follows well-defined, systematic, and mathematical procedures and rules.
Mukhtar Ahmed, Mukhtar Ahmed
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Statistical Model Choice [PDF]
SSRN Electronic Journal, 2015 Variable selection methods and model selection approaches are valuable statistical tools that are indispensable for almost any statistical modeling question. This review first considers the use of information criteria for model selection. Such criteria provide an ordering of the considered models where the best model is selected.
Andre Davids, Gerda Claeskens
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1994
Linear models form the core of classical statistics and are still the basis of much of statistical practice; many modern modelling and analytical techniques build on the methodology developed for linear models.
B. D. Ripley, W. N. Venables
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Linear models form the core of classical statistics and are still the basis of much of statistical practice; many modern modelling and analytical techniques build on the methodology developed for linear models.
B. D. Ripley, W. N. Venables
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