public interface ChiSquareTest
This interface handles only known distributions. If the distribution is
unknown and should be provided by a sample, then the UnknownDistributionChiSquareTest
extended interface should be used instead.
Modifier and Type  Method and Description 

double 
chiSquare(double[] expected,
long[] observed)

double 
chiSquare(long[][] counts)
Computes the ChiSquare statistic associated with a
chisquare test of independence based on the input
counts
array, viewed as a twoway table. 
double 
chiSquareTest(double[] expected,
long[] observed)
Returns the observed significance level, or
pvalue, associated with a
Chisquare goodness of fit test comparing the
observed
frequency counts to those in the expected array. 
boolean 
chiSquareTest(double[] expected,
long[] observed,
double alpha)
Performs a
Chisquare goodness of fit test evaluating the null hypothesis that the observed counts
conform to the frequency distribution described by the expected counts, with
significance level
alpha . 
double 
chiSquareTest(long[][] counts)
Returns the observed significance level, or
pvalue, associated with a
chisquare test of independence based on the input
counts
array, viewed as a twoway table. 
boolean 
chiSquareTest(long[][] counts,
double alpha)
Performs a
chisquare test of independence evaluating the null hypothesis that the classifications
represented by the counts in the columns of the input 2way table are independent of the rows,
with significance level
alpha . 
double chiSquare(double[] expected, long[] observed) throws java.lang.IllegalArgumentException
observed
and expected
frequency counts.
This statistic can be used to perform a ChiSquare test evaluating the null hypothesis that the observed counts follow the expected distribution.
Preconditions:
If any of the preconditions are not met, an
IllegalArgumentException
is thrown.
observed
 array of observed frequency countsexpected
 array of expected frequency countsjava.lang.IllegalArgumentException
 if preconditions are not metdouble chiSquareTest(double[] expected, long[] observed) throws java.lang.IllegalArgumentException, MathException
observed
frequency counts to those in the expected
array.
The number returned is the smallest significance level at which one can reject the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts.
Preconditions:
If any of the preconditions are not met, an
IllegalArgumentException
is thrown.
observed
 array of observed frequency countsexpected
 array of expected frequency countsjava.lang.IllegalArgumentException
 if preconditions are not metMathException
 if an error occurs computing the pvalueboolean chiSquareTest(double[] expected, long[] observed, double alpha) throws java.lang.IllegalArgumentException, MathException
alpha
. Returns true iff the null hypothesis can be rejected
with 100 * (1  alpha) percent confidence.
Example:
To test the hypothesis that observed
follows
expected
at the 99% level, use
chiSquareTest(expected, observed, 0.01)
Preconditions:
0 < alpha < 0.5
If any of the preconditions are not met, an
IllegalArgumentException
is thrown.
observed
 array of observed frequency countsexpected
 array of expected frequency countsalpha
 significance level of the testjava.lang.IllegalArgumentException
 if preconditions are not metMathException
 if an error occurs performing the testdouble chiSquare(long[][] counts) throws java.lang.IllegalArgumentException
counts
array, viewed as a twoway table.
The rows of the 2way table are
count[0], ... , count[count.length  1]
Preconditions:
counts
must have at
least 2 columns and at least 2 rows.
If any of the preconditions are not met, an
IllegalArgumentException
is thrown.
counts
 array representation of 2way tablejava.lang.IllegalArgumentException
 if preconditions are not metdouble chiSquareTest(long[][] counts) throws java.lang.IllegalArgumentException, MathException
counts
array, viewed as a twoway table.
The rows of the 2way table are
count[0], ... , count[count.length  1]
Preconditions:
counts
must have at least 2 columns and
at least 2 rows.
If any of the preconditions are not met, an
IllegalArgumentException
is thrown.
counts
 array representation of 2way tablejava.lang.IllegalArgumentException
 if preconditions are not metMathException
 if an error occurs computing the pvalueboolean chiSquareTest(long[][] counts, double alpha) throws java.lang.IllegalArgumentException, MathException
alpha
. Returns true iff the null hypothesis can be rejected
with 100 * (1  alpha) percent confidence.
The rows of the 2way table are
count[0], ... , count[count.length  1]
Example:
To test the null hypothesis that the counts in
count[0], ... , count[count.length  1]
all correspond to the same underlying probability distribution at the 99% level, use
chiSquareTest(counts, 0.01)
Preconditions:
counts
must have at least 2 columns and
at least 2 rows.
If any of the preconditions are not met, an
IllegalArgumentException
is thrown.
counts
 array representation of 2way tablealpha
 significance level of the testjava.lang.IllegalArgumentException
 if preconditions are not metMathException
 if an error occurs performing the testCopyright © 2010  2019 Adobe. All Rights Reserved