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Mathematical Statistics

Mathematical Statistics

Created by Richard Dudley of the Massachusetts Institute of Technology, this lesson, Mathematical Statistics, is a graduate-level course featuring book chapters and sections presented as lecture notes, problem sets, exams, and a description for an optional term-paper. The course covers: decision theory, estimation, confidence intervals, hypothesis testing, asymptotic efficiency of estimates, exponential families, sequential analysis, and large...

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Keywords:
Asymptotic Efficiency, James-Stein Estimators, Sufficiency, Solari's Example, Mathematics -- Statistics, Exponential Families, M-Estimation, Stein's Phenomenon, Estimation, NSDL, Mathematics, Decision Theory, Neyman Pearson Lemma, Confidence Intervals, Wilks's Theorem, Testing Simple Hypothesis, Large Sample Theory, Bayes Decision Theory, Probability Theory, Stochastic Processes, Lehmann-Scheff'e Property, Sequential Analysis, Convexity
Disciplines:
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More about this material

Material Type:
Open (Access) Textbook
Date Added to MERLOT:
July 11, 2016
Date Modified in MERLOT:
July 11, 2016
Author:
Submitter:
Barbra Bied Sperling
Primary Audience:
College General Ed, College Lower Division, College Upper Division, Graduate School, Professional
Technical Format:
Website
Mobile Compatibility:
Not specified at this time
Language:
English
Cost Involved:
No
Source Code Available:
No
Accessibility Information Available:
Unknown
Creative Commons:
Creative Commons License
This work is licensed under a Attribution-NonCommercial-ShareAlike 3.0 United States

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