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The term replacement cost or replacement value refers to the amount that an entity would have to pay to replace an asset at the present time, according to its current worth. [1] In the insurance industry, "replacement cost" or "replacement cost value" is one of several methods of determining the value of an insured item. Replacement cost is the ...
In statistical process control (SPC), the ¯ and R chart is a type of scheme, popularly known as control chart, used to monitor the mean and range of a normally distributed variables simultaneously, when samples are collected at regular intervals from a business or industrial process. [1]
In statistics, imputation is the process of replacing missing data with substituted values. When substituting for a data point, it is known as "unit imputation"; when substituting for a component of a data point, it is known as "item imputation".
Schematic of Jackknife Resampling. In statistics, the jackknife (jackknife cross-validation) is a cross-validation technique and, therefore, a form of resampling.It is especially useful for bias and variance estimation.
The "chart" actually consists of a pair of charts: one, the individuals chart, displays the individual measured values; the other, the moving range chart, displays the difference from one point to the next.
When selecting items with replacement the selection procedure is to just draw one item at a time (like getting n draws from a multinomial distribution with N elements, each with their own selection probability). If doing a without-replacement sampling, the schema can become more complex.
The low CUSUM value, detecting a negative anomaly, + = (, +) where ω {\displaystyle \omega } is a critical level parameter (tunable, same as threshold T) that's used to adjust the sensitivity of change detection: larger ω {\displaystyle \omega } makes CUSUM less sensitive to the change and vice versa.
Yates's correction should always be applied, as it will tend to improve the accuracy of the p-value obtained. [citation needed] However, in situations with large sample sizes, using the correction will have little effect on the value of the test statistic, and hence the p-value.