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In statistics, an L-estimator (or L-statistic) is an estimator which is a linear combination of order statistics of the measurements. This can be as little as a single point, as in the median (of an odd number of values), or as many as all points, as in the mean.
In general, with a normally-distributed sample mean, Ẋ, and with a known value for the standard deviation, σ, a 100(1-α)% confidence interval for the true μ is formed by taking Ẋ ± e, with e = z 1-α/2 (σ/n 1/2), where z 1-α/2 is the 100(1-α/2)% cumulative value of the standard normal curve, and n is the number of data values in that ...
Fugl-Meyer Assessment (FMA) scale is an index to assess the sensorimotor impairment in individuals who have had stroke. [1] This scale was first proposed by Axel Fugl-Meyer and his colleagues as a standardized assessment test for post-stroke recovery in their paper titled The post-stroke hemiplegic patient: A method for evaluation of physical performance.
The item-total correlation approach is a way of identifying a group of questions whose responses can be combined into a single measure or scale. This is a simple approach that works by ensuring that, when considered across a whole population, responses to the questions in the group tend to vary together and, in particular, that responses to no individual question are poorly related to an ...
Sample variance of x: s 2 x: 11 exact Mean of y: 7.50 to 2 decimal places Sample variance of y: s 2 y: 4.125 ±0.003 Correlation between x and y: 0.816 to 3 decimal places Linear regression line y = 3.00 + 0.500x: to 2 and 3 decimal places, respectively Coefficient of determination of the linear regression: 0.67 to 2 decimal places
Here two scales represent known values and the third is the scale where the result is read off. The simplest such equation is u 1 + u 2 + u 3 = 0 for the three variables u 1 , u 2 and u 3 . An example of this type of nomogram is shown on the right, annotated with terms used to describe the parts of a nomogram.
Confidence bands can be constructed around estimates of the empirical distribution function.Simple theory allows the construction of point-wise confidence intervals, but it is also possible to construct a simultaneous confidence band for the cumulative distribution function as a whole by inverting the Kolmogorov-Smirnov test, or by using non-parametric likelihood methods.
Scale analysis rules as follows: Rule1-First step in scale analysis is to define the domain of extent in which we apply scale analysis. Any scale analysis of a flow region that is not uniquely defined is not valid. Rule2-One equation constitutes an equivalence between the scales of two dominant terms appearing in the equation. For example,