statistics-0.16.4.0: A library of statistical types, data, and functions

Copyright | (c) Praneya Kumar Alexey Khudyakov 2025
License | BSD-3-Clause
Safe Haskell | None
Language | Haskell2010

Statistics.Test.Bartlett

Description

Bartlett's test is used to check that multiple groups of observations come from distributions with equal variances. This test assumes that samples come from normal distribution. If this is not the case it may simple test for non-normality and Levene's (Statistics.Test.Levene) is preferred

    >>> import qualified Data.Vector.Unboxed as VU
    >>> import Statistics.Test.Bartlett
    >>> :{
    let a = VU.fromList [8.88, 9.12, 9.04, 8.98, 9.00, 9.08, 9.01, 8.85, 9.06, 8.99]
        b = VU.fromList [8.88, 8.95, 9.29, 9.44, 9.15, 9.58, 8.36, 9.18, 8.67, 9.05]
        c = VU.fromList [8.95, 9.12, 8.95, 8.85, 9.03, 8.84, 9.07, 8.98, 8.86, 8.98]
    in bartlettTest [a,b,c]
    :}
    Right (Test {testSignificance = mkPValue 1.1254782518843598e-5, testStatistics = 22.789434813726768, testDistribution = chiSquared 2})

Synopsis

- bartlettTest :: Vector v Double => [v Double] -> Either String (Test ChiSquared)
- data ChiSquared
- chiSquared :: Int -> ChiSquared

# Documentation

bartlettTest :: Vector v Double => [v Double] -> Either String (Test ChiSquared) Source #

Perform Bartlett's test for equal variances. The input is a list of vectors, where each vector represents a group of observations.

data ChiSquared Source #

Chi-squared distribution

#### Instances

Instances details

FromJSON ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods parseJSON :: Value -> Parser ChiSquared Source # parseJSONList :: Value -> Parser [ChiSquared] Source # omittedField :: Maybe ChiSquared Source #
ToJSON ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods toJSON :: ChiSquared -> Value Source # toEncoding :: ChiSquared -> Encoding Source # toJSONList :: [ChiSquared] -> Value Source # toEncodingList :: [ChiSquared] -> Encoding Source # omitField :: ChiSquared -> Bool Source #
Binary ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods put :: ChiSquared -> Put Source # get :: Get ChiSquared Source # putList :: [ChiSquared] -> Put Source #
Data ChiSquared Source # |

Instance details

Defined in Statistics.Distribution.ChiSquared

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> ChiSquared -> c ChiSquared Source #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c ChiSquared Source #

toConstr :: ChiSquared -> Constr Source #

dataTypeOf :: ChiSquared -> DataType Source #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c ChiSquared) Source #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c ChiSquared) Source #

gmapT :: (forall b. Data b => b -> b) -> ChiSquared -> ChiSquared Source #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> ChiSquared -> r Source #

gmapQr :: forall r r'. (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> ChiSquared -> r Source #

gmapQ :: (forall d. Data d => d -> u) -> ChiSquared -> [u] Source #

gmapQi :: Int -> (forall d. Data d => d -> u) -> ChiSquared -> u Source #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> ChiSquared -> m ChiSquared Source #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> ChiSquared -> m ChiSquared Source #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> ChiSquared -> m ChiSquared Source #

Generic ChiSquared Source # |

Instance details

Defined in Statistics.Distribution.ChiSquared

Associated Types

type Rep ChiSquared |
Instance details Defined in Statistics.Distribution.ChiSquared type Rep ChiSquared = D1 ('MetaData "ChiSquared" "Statistics.Distribution.ChiSquared" "statistics-0.16.4.0-CwUrX7BVOPjWfNRlOxuPU" 'True) (C1 ('MetaCons "ChiSquared" 'PrefixI 'True) (S1 ('MetaSel ('Just "chiSquaredNDF") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 Int)))

Methods

from :: ChiSquared -> Rep ChiSquared x Source #

to :: Rep ChiSquared x -> ChiSquared Source #

Read ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods readsPrec :: Int -> ReadS ChiSquared Source # readList :: ReadS [ChiSquared] Source # readPrec :: ReadPrec ChiSquared Source # readListPrec :: ReadPrec [ChiSquared] Source #
Show ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods showsPrec :: Int -> ChiSquared -> ShowS Source # show :: ChiSquared -> String Source # showList :: [ChiSquared] -> ShowS Source #
Eq ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods (==) :: ChiSquared -> ChiSquared -> Bool Source # (/=) :: ChiSquared -> ChiSquared -> Bool Source #
ContDistr ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods density :: ChiSquared -> Double -> Double Source # logDensity :: ChiSquared -> Double -> Double Source # quantile :: ChiSquared -> Double -> Double Source # complQuantile :: ChiSquared -> Double -> Double Source #
ContGen ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods genContVar :: StatefulGen g m => ChiSquared -> g -> m Double Source #
Distribution ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods cumulative :: ChiSquared -> Double -> Double Source # complCumulative :: ChiSquared -> Double -> Double Source #
Entropy ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods entropy :: ChiSquared -> Double Source #
MaybeEntropy ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods maybeEntropy :: ChiSquared -> Maybe Double Source #
MaybeMean ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods maybeMean :: ChiSquared -> Maybe Double Source #
MaybeVariance ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods maybeVariance :: ChiSquared -> Maybe Double Source # maybeStdDev :: ChiSquared -> Maybe Double Source #
Mean ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods mean :: ChiSquared -> Double Source #
Variance ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods variance :: ChiSquared -> Double Source # stdDev :: ChiSquared -> Double Source #
type Rep ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared type Rep ChiSquared = D1 ('MetaData "ChiSquared" "Statistics.Distribution.ChiSquared" "statistics-0.16.4.0-CwUrX7BVOPjWfNRlOxuPU" 'True) (C1 ('MetaCons "ChiSquared" 'PrefixI 'True) (S1 ('MetaSel ('Just "chiSquaredNDF") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 Int)))

chiSquared :: Int -> ChiSquared Source #

Construct chi-squared distribution. Number of degrees of freedom must be positive.