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  2. Grand mean - Wikipedia

    en.wikipedia.org/wiki/Grand_mean

    The grand mean or pooled mean is the average of the means of several subsamples, as long as the subsamples have the same number of data points. [1] For example, consider several lots, each containing several items. The items from each lot are sampled for a measure of some variable and the means of the measurements from each lot are computed ...

  3. Pooled variance - Wikipedia

    en.wikipedia.org/wiki/Pooled_variance

    In statistics, pooled variance (also known as combined variance, composite variance, or overall variance, and written ) is a method for estimating variance of several different populations when the mean of each population may be different, but one may assume that the variance of each population is the same. The numerical estimate resulting from ...

  4. Welch–Satterthwaite equation - Wikipedia

    en.wikipedia.org/wiki/Welch–Satterthwaite_equation

    In statistics and uncertainty analysis, the Welch–Satterthwaite equation is used to calculate an approximation to the effective degrees of freedom of a linear combination of independent sample variances, also known as the pooled degrees of freedom, [1] [2] corresponding to the pooled variance.

  5. Intraclass correlation - Wikipedia

    en.wikipedia.org/wiki/Intraclass_correlation

    The key difference between this ICC and the interclass (Pearson) correlation is that the data are pooled to estimate the mean and variance. The reason for this is that in the setting where an intraclass correlation is desired, the pairs are considered to be unordered.

  6. Inverse-variance weighting - Wikipedia

    en.wikipedia.org/wiki/Inverse-variance_weighting

    For normally distributed random variables inverse-variance weighted averages can also be derived as the maximum likelihood estimate for the true value. Furthermore, from a Bayesian perspective the posterior distribution for the true value given normally distributed observations and a flat prior is a normal distribution with the inverse-variance weighted average as a mean and variance ().

  7. 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.

  8. Student's t-test - Wikipedia

    en.wikipedia.org/wiki/Student's_t-test

    The mean word.recall in the 1 drug.dose group is 6. The difference between treatment groups in the mean word.recall is 6 – 2 = 4. The difference in word.recall between drug doses is significant (p=0.00805). Perform a linear regression of the same data. Calculations may be performed using the R function lm() for a linear model.

  9. Estimation of covariance matrices - Wikipedia

    en.wikipedia.org/wiki/Estimation_of_covariance...

    It naturally breaks down into the part related to the estimation of the mean, and to the part related to the estimation of the variance. The first order condition for maximum, d ln ⁡ L ( μ , Σ ) = 0 {\displaystyle d\ln {\mathcal {L}}(\mu ,\Sigma )=0} , is satisfied when the terms multiplying d μ {\displaystyle d\mu } and d Σ ...