Introduction to the Theory of Statistics |
Contents
Introduction | 1 |
Discrete Random Variables | 53 |
Interval Estimation | 248 |
Copyright | |
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95 per cent a₁ approximately balls binomial cent confidence interval chi-square distribution coefficient compute conditional distribution covariance cumulative distribution decision function defined Definition degrees of freedom denoted density f(x density function drawn equal error event example expected value gamma distribution given H₁ hence independent integral John Wiley joint density large samples Let X1 likelihood-ratio likelihood-ratio test linear loss function marginal density matrix maximum-likelihood estimator mean and variance method minimum-variance unbiased estimator moment generating function n₁ n₂ normal density normal distribution normal equations normal population normal with mean null hypothesis observations obtain outcomes p₁ Prob probability problem random sample random variable sample mean sample space sufficient statistic Suppose Theorem theory tossed Type I error unbiased estimator unknown parameters variance o² variate vector w₂ Wiley & Sons x₁ y₁ μ₁ σ²