MIME
发表于 2025-3-25 03:34:34
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围裙
发表于 2025-3-25 10:24:33
ProbabilityProbability is a mathematical language for quantifying uncertainty. In this Chapter we introduce the basic concepts underlying probability theory. We begin with the sample space, which is the set of possible outcomes.
inhibit
发表于 2025-3-25 12:44:38
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可耕种
发表于 2025-3-25 16:22:21
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Externalize
发表于 2025-3-25 23:19:48
InequalitiesInequalities are useful for bounding quantities that might otherwise be hard to compute. They will also be used in the theory of convergence which is discussed in the next chapter. Our first inequality is Markov’s inequality.
zonules
发表于 2025-3-26 01:28:54
Models, Statistical Inference and LearningStatistical inference, or “learning” as it is called in computer science, is the process of using data to infer the distribution that generated the data. A typical statistical inference question is:
MEEK
发表于 2025-3-26 06:40:23
Estimating the CDF and Statistical FunctionalsThe first inference problem we will consider is nonparametric estimation of the CDF .. Then we will estimate statistical functionals, which are functions of CDF, such as the mean, the variance, and the correlation. The nonparametric method for estimating functionals is called the plug-in method.
保存
发表于 2025-3-26 11:03:19
The BootstrapThe . is a method for estimating standard errors and computing confidence intervals. Let .. = .(..,…, ..) be a ., that is, .. is any function of the data. Suppose we want to know V.(..), the variance of ... We have written V. to emphasize that the variance usually depends on the unknown distribution function ..
forestry
发表于 2025-3-26 12:38:20
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认为
发表于 2025-3-26 18:46:01
Hypothesis Testing and p-valuesSuppose we want to know if exposure to asbestos is associated with lung disease. We take some rats and randomly divide them into two groups. We expose one group to asbestos and leave the second group unexposed. Then we compare the disease rate in the two groups. Consider the following two hypotheses: