Statistical InferenceDiscusses both theoretical statistics and the practical applications of the theoretical developments. Includes a large numer of exercises covering both theory and applications. |
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analysis ANOVA apply approximation assume assumptions Bayes binomial blocks calculate called Chapter complete conditional confidence confidence interval confidence set constant continuous contrasts decision rule defined definition depend derived discussed distribution equal error estimator Example Exercise exists expected experiment expression fact function given gives hence hypothesis independent Inequality inference integral interest interval invariant joint known least likelihood linear loss mean measure method minimal minimax normal Note observed obtain parameter particular population possible prior probability problem Proof properties prove random sample random variables region regression reject relationship result risk function sample mean satisfies Show similar space squares statistic sufficient statistic Suppose Theorem transformation treatment true types unbiased estimator usually values variance verify versus H₁ X₁ Y₁