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A graph showing variation of quantum efficiency with wavelength of a CCD chip from Wide Field and Planetary Camera 2, formerly installed on the Hubble Space Telescope.. The term quantum efficiency (QE) may apply to incident photon to converted electron (IPCE) ratio [1] of a photosensitive device, or it may refer to the TMR effect of a magnetic tunnel junction.
The DQE is the ratio of what an image is worth to what it cost in terms of numbers of Poisson-distributed quanta: D Q E = N E Q q {\displaystyle \mathrm {DQE} ={\frac {\mathrm {NEQ} }{q}}} . In this sense the DQE describes how effectively an imaging system captures the information content available in an x-ray image relative to an ideal detector.
In statistics, an effect size is a value measuring the strength of the relationship between two variables in a population, or a sample-based estimate of that quantity. It can refer to the value of a statistic calculated from a sample of data, the value of one parameter for a hypothetical population, or to the equation that operationalizes how statistics or parameters lead to the effect size ...
First, with a data sample of length n, the data analyst may run the regression over only q of the data points (with q < n), holding back the other n – q data points with the specific purpose of using them to compute the estimated model’s MSPE out of sample (i.e., not using data that were used in the model estimation process).
The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]
Estimation statistics, or simply estimation, is a data analysis framework that uses a combination of effect sizes, confidence intervals, precision planning, and meta-analysis to plan experiments, analyze data and interpret results. [1]
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Ordinary least squares regression of Okun's law.Since the regression line does not miss any of the points by very much, the R 2 of the regression is relatively high.. In statistics, the coefficient of determination, denoted R 2 or r 2 and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the independent variable(s).