Throughout, the text concentrates on concepts, rather than mathematical detail, while maintaining appropriate levels of formality. Each chapter ends with a set of accessible problems. Essentials of Statistical
ESSENTIALS OF STATISTICAL INFERENCE - ScienceDirectThesis (Ph. D.)--Virginia Polytechnic Institute and State University, 1995. Vita.Includes bibliographical references (leaves 134-141).doi:10.1016/B978-0-12-374097-7.00004-1J. Andrew RoyleRobert M. Dorazio...
text provides both basic material on the main approaches to inference, as well as more advanced material on developments in statistical theory, including: material on Bayesian computation, such as MCMC, higher-order likelihood theory, predictive inference, bootstrap methods and conditional inference. It...
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Control group is always needed to support or refute an inference.12 Case control studies compare cases with controls with respect to exposure and are useful to study multiple outcomes of a single disease. They are easier to perform and logistically more feasible.15 Case control studies do not ...
The book covers detailed examples and large hybrid datasets to help you grasp essential statistical techniques for data collection, data munging and analysis, visualization, and reporting activities. You will also gain an understanding of advanced data science topics such as machine learning algorithms,...
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(2005) Essentials of Statistical Inference, Cambridge University Press.Young, G.A. and Smith, R.L. (2005). Essentials of Statistical Inference. Cambridge University Press, Cambridge.Young, G. and Smith, R. L. 2005. Essentials of Statistical Inference. Cambridge University Press....