Faster access than browser!
26 relations: Anderson–Darling test, Biometrika, Covariance matrix, Cramér–von Mises criterion, D'Agostino's K-squared test, Expected value, Independent and identically distributed random variables, Kolmogorov–Smirnov test, Lilliefors test, Martin Wilk, Monte Carlo method, Normal distribution, Normal probability plot, Normality test, Null hypothesis, Order statistic, P-value, Power (statistics), Q–Q plot, Sample (statistics), Samuel Sanford Shapiro, Statistical hypothesis testing, Statistical significance, Statistics, Test statistic, Type I and type II errors.
Anderson–Darling test
The Anderson–Darling test is a statistical test of whether a given sample of data is drawn from a given probability distribution.
New!!: Shapiro–Wilk test and Anderson–Darling test · See more »
Biometrika
Biometrika is a peer-reviewed scientific journal published by Oxford University Press for the Biometrika Trust.
New!!: Shapiro–Wilk test and Biometrika · See more »
Covariance matrix
In probability theory and statistics, a covariance matrix (also known as dispersion matrix or variance–covariance matrix) is a matrix whose element in the i, j position is the covariance between the i-th and j-th elements of a random vector.
New!!: Shapiro–Wilk test and Covariance matrix · See more »
Cramér–von Mises criterion
In statistics the Cramér–von Mises criterion is a criterion used for judging the goodness of fit of a cumulative distribution function F^* compared to a given empirical distribution function F_n, or for comparing two empirical distributions.
New!!: Shapiro–Wilk test and Cramér–von Mises criterion · See more »
D'Agostino's K-squared test
In statistics, D’Agostino’s K2 test, named for Ralph D'Agostino, is a goodness-of-fit measure of departure from normality, that is the test aims to establish whether or not the given sample comes from a normally distributed population.
New!!: Shapiro–Wilk test and D'Agostino's K-squared test · See more »
Expected value
In probability theory, the expected value of a random variable, intuitively, is the long-run average value of repetitions of the experiment it represents.
New!!: Shapiro–Wilk test and Expected value · See more »
Independent and identically distributed random variables
In probability theory and statistics, a sequence or other collection of random variables is independent and identically distributed (i.i.d. or iid or IID) if each random variable has the same probability distribution as the others and all are mutually independent.
New!!: Shapiro–Wilk test and Independent and identically distributed random variables · See more »
Kolmogorov–Smirnov test
In statistics, the Kolmogorov–Smirnov test (K–S test or KS test) is a nonparametric test of the equality of continuous, one-dimensional probability distributions that can be used to compare a sample with a reference probability distribution (one-sample K–S test), or to compare two samples (two-sample K–S test).
New!!: Shapiro–Wilk test and Kolmogorov–Smirnov test · See more »
Lilliefors test
In statistics, the Lilliefors test is a normality test based on the Kolmogorov–Smirnov test.
New!!: Shapiro–Wilk test and Lilliefors test · See more »
Martin Wilk
Martin Bradbury Wilk, (18 December 1922 – 19 February 2013) was a Canadian statistician, academic, and the former Chief Statistician of Canada.
New!!: Shapiro–Wilk test and Martin Wilk · See more »
Monte Carlo method
Monte Carlo methods (or Monte Carlo experiments) are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results.
New!!: Shapiro–Wilk test and Monte Carlo method · See more »
Normal distribution
In probability theory, the normal (or Gaussian or Gauss or Laplace–Gauss) distribution is a very common continuous probability distribution.
New!!: Shapiro–Wilk test and Normal distribution · See more »
Normal probability plot
The normal probability plot is a graphical technique to identify substantive departures from normality.
New!!: Shapiro–Wilk test and Normal probability plot · See more »
Normality test
In statistics, normality tests are used to determine if a data set is well-modeled by a normal distribution and to compute how likely it is for a random variable underlying the data set to be normally distributed.
New!!: Shapiro–Wilk test and Normality test · See more »
Null hypothesis
In inferential statistics, the term "null hypothesis" is a general statement or default position that there is no relationship between two measured phenomena, or no association among groups.
New!!: Shapiro–Wilk test and Null hypothesis · See more »
Order statistic
In statistics, the kth order statistic of a statistical sample is equal to its kth-smallest value.
New!!: Shapiro–Wilk test and Order statistic · See more »
P-value
In statistical hypothesis testing, the p-value or probability value or asymptotic significance is the probability for a given statistical model that, when the null hypothesis is true, the statistical summary (such as the sample mean difference between two compared groups) would be the same as or of greater magnitude than the actual observed results.
New!!: Shapiro–Wilk test and P-value · See more »
Power (statistics)
The power of a binary hypothesis test is the probability that the test correctly rejects the null hypothesis (H0) when a specific alternative hypothesis (H1) is true.
New!!: Shapiro–Wilk test and Power (statistics) · See more »
Q–Q plot
In statistics, a Q–Q (quantile-quantile) plot is a probability plot, which is a graphical method for comparing two probability distributions by plotting their quantiles against each other.
New!!: Shapiro–Wilk test and Q–Q plot · See more »
Sample (statistics)
In statistics and quantitative research methodology, a data sample is a set of data collected and/or selected from a statistical population by a defined procedure.
New!!: Shapiro–Wilk test and Sample (statistics) · See more »
Samuel Sanford Shapiro
Samuel Sanford Shapiro (born July 13, 1930) is an American statistician and engineer.
New!!: Shapiro–Wilk test and Samuel Sanford Shapiro · See more »
Statistical hypothesis testing
A statistical hypothesis, sometimes called confirmatory data analysis, is a hypothesis that is testable on the basis of observing a process that is modeled via a set of random variables.
New!!: Shapiro–Wilk test and Statistical hypothesis testing · See more »
Statistical significance
In statistical hypothesis testing, a result has statistical significance when it is very unlikely to have occurred given the null hypothesis.
New!!: Shapiro–Wilk test and Statistical significance · See more »
Statistics
Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data.
New!!: Shapiro–Wilk test and Statistics · See more »
Test statistic
A test statistic is a statistic (a quantity derived from the sample) used in statistical hypothesis testing.
New!!: Shapiro–Wilk test and Test statistic · See more »
Type I and type II errors
In statistical hypothesis testing, a type I error is the rejection of a true null hypothesis (also known as a "false positive" finding), while a type II error is failing to reject a false null hypothesis (also known as a "false negative" finding).
New!!: Shapiro–Wilk test and Type I and type II errors · See more »
Redirects here:
Shapiro Wilk test, Shapiro wilk, Shapiro wilk normality test, Shapiro-Wilk, Shapiro-Wilk test, Shapiro-Wilks test, Shapiro-wilk normality test, W statistic, W-statistic, Wilk-Shapiro test, Wilk–Shapiro test.
References
[1] https://en.wikipedia.org/wiki/Shapiro–Wilk_test
