Before combining data, however, it would be prudent to test whether the data sets are compatible with a common dose-response model. If they are not, it could be concluded that an underlying biological factor is
Statistical significance is used to gauge the likelihood that a relationship exists between two variables, based on observational data. Contrary to popular misconception, this does not measure the probability that the two variables are causally related. Rather, it measures the probability that the obser...
Specifically, the distance between the data and the model prediction is measured using atest statistic(such as a t-statistic or a Chi squared statistic). ThePvalue is then the probability that the chosen test statistic would have beenat leastas large as its observed value ifeverymodel assumptio...
Classical estimation methods limit inferences to the information contained in the life test data themselves, although limited subjective judgments must be made regarding the estimator to use, confidence level, and so forth. The primary distinction between classical and Bayesian methods is that in the ...
This package facilitates this recent movements by providing the necessary methodological tools. The Network Comparison Test (NCT) uses resampling-based permutation testing to compare network structures from two independent, cross-sectional data sets on invariance of 1) network structure, 2) edge (connect...
Many statistical tests have underlying assumptions about the population data. But, what happens if you violate those assumptions? This is when you might need to use a non-parametric test to answer your statistical question. Non-parametric refers to a type of statistical analysis that does not mak...
provide a set of data from those who read the publication or view the Internet site, which is a first category of selection, and from this set the individuals who choose to respond are then self-selecting. This group may represent those with a particular viewpoint, those with strong views ...
rnaseqde Perform differential expression analysis on RNA-seq count data knnimpute Impute missing data using nearest-neighbor method crossvalind Generate indices for training and test sets classperf Evaluate classifier performanceClasses NegativeBinomialTest Unpaired hypothesis test result CuffCompareOptions Option...
pairs of classifiers, as if the tests for multiple comparisons, such as ANOVA and Friedman test are yet to be invented. The core of the paper is the study of the statistical tests that could be (or already are) used for comparing two or more classifiers on multiple data sets. Form...
Parametric statistical tests, such as the independent samples t-test, which are designed to look at the difference between central tendencies, for example, in reading age between two classes of children, will compare the means of the different data sets. The mean, or, more precisely, the ...