It also covers statistical techniques such as Box-Wetz Ratio, Levene's Test, Pearson R 2 , and autocovariance. Quantile plots (Q plots) are used to compare the distributions of two sets of values. Two related parameters, known as skewness and kurtosis, can be used to determine how close ...
Choosing the right test to compare measurements is a bit tricky, as you must choose between two families of tests: parametric and nonparametric. Many -statistical test are based upon the assumption that the data are sampled from a Gaussian distribution. These tests are referred to as parametric ...
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...
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...
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 ...
Z-test This parametric test analyzes data when the sample size is small and the population standard deviation (σ) is known. It determines whether two population means are different and measures the relationship between two variables. Business owners use it to compare two means, calculate confidence...
Table 1 Statistical hypothesis test methods Full size table Parametric statistical tests often have a number of assumptions on data characteristics for comparison. For example, analysis of variance (ANOVA) requires the data to meet the following three conditions: independence, normality and homogeneity ...
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...