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  2. Yates analysis - Wikipedia

    en.wikipedia.org/wiki/Yates_Analysis

    The cumulative residual standard deviation that results from the model using the current term plus all terms preceding that term. That is, response = constant + 0.5 ( a l l e f f e c t e s t i m a t e s d o w n t o a n d i n c l u d i n g t h e e f f e c t o f i n t e r e s t ) {\displaystyle {\textrm {response}}={\textrm {constant}}+0.5\mathrm ...

  3. Standard deviation - Wikipedia

    en.wikipedia.org/wiki/Standard_deviation

    The mean and the standard deviation of a set of data are descriptive statistics usually reported together. In a certain sense, the standard deviation is a "natural" measure of statistical dispersion if the center of the data is measured about the mean. This is because the standard deviation from the mean is smaller than from any other point.

  4. Chauvenet's criterion - Wikipedia

    en.wikipedia.org/wiki/Chauvenet's_criterion

    The idea behind Chauvenet's criterion finds a probability band that reasonably contains all n samples of a data set, centred on the mean of a normal distribution.By doing this, any data point from the n samples that lies outside this probability band can be considered an outlier, removed from the data set, and a new mean and standard deviation based on the remaining values and new sample size ...

  5. x̅ and s chart - Wikipedia

    en.wikipedia.org/wiki/X̅_and_s_chart

    Therefore, several authors recommend using a single chart that can simultaneously monitor ¯ and S. [8] McCracken, Chackrabori and Mukherjee [9] developed one of the most modern and efficient approach for jointly monitoring the Gaussian process parameters, using a set of reference sample in absence of any knowledge of true process parameters.

  6. Algorithms for calculating variance - Wikipedia

    en.wikipedia.org/wiki/Algorithms_for_calculating...

    Algorithms for calculating variance play a major role in computational statistics.A key difficulty in the design of good algorithms for this problem is that formulas for the variance may involve sums of squares, which can lead to numerical instability as well as to arithmetic overflow when dealing with large values.

  7. Prediction interval - Wikipedia

    en.wikipedia.org/wiki/Prediction_interval

    For example, to calculate the 95% prediction interval for a normal distribution with a mean (μ) of 5 and a standard deviation (σ) of 1, then z is approximately 2. Therefore, the lower limit of the prediction interval is approximately 5 ‒ (2⋅1) = 3, and the upper limit is approximately 5 + (2⋅1) = 7, thus giving a prediction interval of ...

  8. Shewhart individuals control chart - Wikipedia

    en.wikipedia.org/wiki/Shewhart_individuals...

    Many software packages will, given the individuals data, perform all of the needed calculations and plot the results. Care should be taken to ensure that the control limits are correctly calculated, per the above and standard texts on SPC.

  9. Unbiased estimation of standard deviation - Wikipedia

    en.wikipedia.org/wiki/Unbiased_estimation_of...

    Bias in standard deviation for autocorrelated data. The figure shows the ratio of the estimated standard deviation to its known value (which can be calculated analytically for this digital filter), for several settings of α as a function of sample size n. Changing α alters the variance reduction ratio of the filter, which is known to be