Category
page 1Statistical tests
analysis of variance
collection of statistical models used to analyze the differences between group means and their associated procedures
Student's t-test
statistical method
Spearman's rank correlation coefficient
nonparametric measure of rank correlation
F-test
thumb|An F-test pdf with d1 and d2 = 10, at a significance level of 0.05. (Red shaded region indicates the critical region)
An F-test is a statistical test that compares variances. It is used to determine if the variances of two samples, or if the ratios of variances among multiple samples, are significantly different. The test calculates a statistic, represented by the random variable F, and checks if it follows an F-distribution. This check is valid if the null hypothesis is true and standard assumptions about the errors (ε) in the data hold.
Mann–Whitney U test
nonparametric test of the null hypothesis that, for randomly picked values X and Y from 2 populations, Pr(X>Y)=Pr(Y>X)
Z-test
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A '''Z-test' is any statistical test for which the distribution of the test statistic under the null hypothesis can be approximated by a normal distribution. Z-test tests the mean of a distribution. For each significance level in the confidence interval, the Z''-test has a single critical value (for example, 1.96 for 5% two-tailed), which makes it more convenient than the Student's t-test whose critical values are defined by the sample size (through the corresponding degrees of freedom). Both the Z-test and Student's t-test have similarities in that they both help determine the signifi
Kruskal–Wallis one-way analysis of variance
non-parametric method for testing whether samples originate from the same distribution
likelihood-ratio test
statistical test used for comparing the goodness of fit of two statistical models
Wilcoxon signed-rank test
non-parametric statistical hypothesis test used to compare two related samples to assess whether their population mean ranks differ
Levene's test
Test in statistics
kendall tau rank correlation
type of statistic
Neyman–Pearson lemma
approach in statistical testing
Sign test
statistical test with teststatistic the number of signs of one type
Friedman test
non-parametric statistical test
Wald–Wolfowitz runs test
nonparametric test of the null hypothesis that two samples have been taken from identical populations, based on whether the number of runs or sequences in an ordering is random
median test
comparative statistical test
Breusch–Pagan test
statistical test
Wald test
statistical test based on a weighed difference between estimate and hypothesis
Chauvenet's criterion
means of assessing whether a data point is flawed
binomial test
test of significance
White test
statistical test
Cochran's Q test
Statistical test
Bartlett's test
statistical test
one-way analysis of variance
statistical test
Hausman test
statistical hypothesis test in econometrics
Tukey's range test
statistical test for multiple comparisons
Welch's t-test
statistical test of whether two populations have equal means
one- and two-tailed tests
alternative ways of computing the statistical significance of a parameter inferred from a data set
Grubbs' test for outliers
statistical test
Cochran's C test
variance outlier test
Kuiper's test
statistical test
Dixon's Q test
criterion for identification and rejection of outliers
Mantel test
Statistical test
permutation test
exact statistical hypothesis test
Goldfeld–Quandt test
test proposed by Stephen Goldfeld and Richard Quandt
Goodman and Kruskal's gamma
statistic for rank correlation
Kaiser Meyer Olkin test
randomness tests
analyzing a set of data to see if it can be described as random (patternless)
Phillips–Perron test
statistical test
Mauchly's sphericity test
statistical test
Score test
statistical test based on the gradient of the likelihood function
GRIM test
statistical consistency test
Brown–Forsythe test
statistical test for equality of variances
Ramsey RESET test
statistical test for model misspecification