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The term "Z-test" is often used to refer specifically to the one-sample location test comparing the mean of a set of measurements to a given constant when the sample variance is known. For example, if the observed data X 1, ..., X n are (i) independent, (ii) have a common mean μ, and (iii) have a common variance σ 2, then the sample average X ...
where R 1 = N 11 + N 12 + N 13, and C 1 = N 11 + N 21, etc. . The trend test statistic is = (), where the t i are weights, and the difference N 1i R 2 −N 2i R 1 can be seen as the difference between N 1i and N 2i after reweighting the rows to have the same total.
Simple back-of-the-envelope test takes the sample maximum and minimum and computes their z-score, or more properly t-statistic (number of sample standard deviations that a sample is above or below the sample mean), and compares it to the 68–95–99.7 rule: if one has a 3σ event (properly, a 3s event) and substantially fewer than 300 samples, or a 4s event and substantially fewer than 15,000 ...
Comparison of the various grading methods in a normal distribution, including: standard deviations, cumulative percentages, percentile equivalents, z-scores, T-scores. In statistics, the standard score is the number of standard deviations by which the value of a raw score (i.e., an observed value or data point) is above or below the mean value of what is being observed or measured.
The application of Fisher's transformation can be enhanced using a software calculator as shown in the figure. Assuming that the r-squared value found is 0.80, that there are 30 data [clarification needed], and accepting a 90% confidence interval, the r-squared value in another random sample from the same population may range from 0.656 to 0.888.
In bootstrap-resamples, the 'population' is in fact the sample, and this is known; hence the quality of inference of the 'true' sample from resampled data (resampled → sample) is measurable. More formally, the bootstrap works by treating inference of the true probability distribution J , given the original data, as being analogous to an ...
For example, if the data is in CSV form (text with commas between values), the program recognizes the format and creates a data set from the CSV file. Finally, the program can be used to do some analysis. In this analysis menu, the variables of interest can be selected, along with other options. Then the analysis is run and results are obtained.
The Z-factor defines a characteristic parameter of the capability of hit identification for each given assay. The following categorization of HTS assay quality by the value of the Z-Factor is a modification of Table 1 shown in Zhang et al. (1999); [2] note that the Z-factor cannot exceed one.