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A course in large sample theory Thomas S. Ferguson
Publisher: Chapman & Hall

Hence, the dependence condition (2.3) allows a stronger dependence within a larger class of random variables and demands more independence within a smaller class. Ferguson, T.S., A Course in Large Sample Theory. €�On an Absolute Criterion for Fitting Frequency Curves. Written by one of the main figures in twentieth century statistics, this book provides a unified treatment of first-order large-sample theory. A Course in Large Sample Theory. Feuerverger, A., A consistent test for bivariate dependence. Asymptotic Theory: Large sample theory, convergence and approximation. This course focuses on drawing large sample inferences about "parameters" in statistical models. A Course in Large Sample Theory (CRC/C&h Texts in Statistical Science) by Thomas S. Chapman and Hall, London, 1996. The course will be divided into three main sections. IMPRINT London : Chapman & Hall, 1996. Description: A first course in the theory of statistics, to follow STAT 516. Not mathematically advanced, but covers a large volume of material. TITLE A course in large sample theory. In statistics, we are interested in the properties of particular random variables (or. Ferguson, A Course in Large Sample Theory, Chapman & Hall, New York, NY, USA, 1996. €�estimators”), which are functions of our data. The central limit theorem is one of the most remarkable results of the theory of probability [1], which is critical to understand inferential statistics and hypothesis testing [2, 3].