Hypothesis Testing Package
This package contains functions for computing confidence intervals from data and -values and confidence intervals for distributions related to the normal distribution.
Given a test statistic in terms of the normal, , Student's , or F-ratio distribution, a -value can be computed using the appropriate -value function. For example, NormalPValue computes a -value for a test statistic using a normal distribution with mean zero and unit variance. A two-sided -value can be obtained by setting TwoSided->True.
|NormalPValue[teststat]||give the -value for teststat in terms of the normal distribution with mean 0 and unit variance|
|StudentTPValue[teststat,dof]||give the -value for teststat in terms of Student's distribution with dof degrees of freedom|
|ChiSquarePValue[teststat,dof]||give the -value for teststat in terms of the distribution with dof degrees of freedom|
|FRatioPValue[teststat,numdof,dendof]||give the -value for teststat in terms of the F-ratio distribution with numdof numerator and dendof denominator degrees of freedom|
Functions for -values of test statistics.
A confidence interval gives bounds within which a parameter value is expected to lie with a certain probability. Interval estimation of a parameter is often useful in observing the accuracy of an estimator as well as in making statistical inferences about the parameter in question.
MeanCI and MeanDifferenceCI provide confidence intervals of means and differences of means based on the central limit theorem.
|MeanCI[list]||give a confidence interval for the population mean estimated from list|
|MeanDifferenceCI[list1,list2]||give a confidence interval for the difference between the population means estimated from list1 and list2|
Confidence intervals for means.
Assumptions about variances of the populations from which the data were sampled will affect the distribution of the parameter estimate. The KnownVariance and EqualVariances options can be used to specify assumptions about population variances.
|KnownVariance||None||value of the known population variance|
Option for MeanCI and MeanDifferenceCI.
Confidence intervals for the mean and for the difference between means are based on a normal distribution if the population variances are assumed known.
Intervals for the mean are based on Student's distribution with degrees of freedom when the population variance must be estimated from a list of elements.
|EqualVariances||False||whether the unknown population variances are assumed equal|
Option for MeanDifferenceCI.
Confidence intervals for the difference between means are also based on Student's distribution if the variances are not known. If the variances are assumed equal, MeanDifferenceCI is based on Student's distribution with Length[list1]+Length[list2]-2 degrees of freedom. If the population variances are not assumed equal, Welch's approximation for the degrees of freedom is used.
VarianceCI and VarianceRatioCI provide tests of variances for normally distributed samples.
|VarianceCI[list]||give a confidence interval for the population variance estimated from list|
|VarianceRatioCI[list1,list2]||give a confidence interval for the ratio of the population variances estimated from list1 and from list2|
Confidence intervals for variances.
The variance confidence interval is based on a distribution and the variance ratio confidence interval is based on an F-ratio distribution.
The default confidence level for confidence interval functions is .95. Other levels can be specified via the ConfidenceLevel option.
|ConfidenceLevel||.95||confidence level for the interval|
Option for all confidence interval functions.
Given an estimate of the mean, variance, or ratio of variances and necessary standard deviations or degrees of freedom, confidence intervals can also be obtained for normal, chi-square, Student's , or F-ratio distributions.
|NormalCI[mean,sd]||give the confidence interval centered at mean with standard deviation sd|
|StudentTCI[mean,se,dof]||give the confidence interval centered at mean with standard error se and dof degrees of freedom|
|ChiSquareCI[variance,dof]||give the confidence interval for the population variance given the sample variance variance and dof degrees of freedom|
|FRatioCI[ratio,numdof,dendof]||give the confidence interval for the ratio of population variances, given the ratio of sample variances ratio and where the sample variances in the numerator and denominator have numdof and dendof degrees of freedom|
Confidence intervals given sample estimates.