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test: add tests
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‎lib/node_modules/@stdlib/stats/strided/dztest/test/test.dztest.js

Lines changed: 209 additions & 1 deletion
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@@ -21,9 +21,20 @@
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// MODULES //
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var tape = require( 'tape' );
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var Float64Results = require( '@stdlib/stats/base/ztest/one-sample/results/float64' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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var dfill = require( '@stdlib/blas/ext/base/dfill' ).ndarray;
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var normalFactory = require( '@stdlib/random/array/normal' ).factory;
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var dztest = require( './../lib/dztest.js' );
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// VARIABLES //
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var normal = normalFactory({
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'seed': 12345
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});
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// TESTS //
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tape( 'main export is a function', function test( t ) {
@@ -32,4 +43,201 @@ tape( 'main export is a function', function test( t ) {
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t.end();
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});
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// FIXME: add tests
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tape( 'the function performs a one-sample Z-test over a strided array (alternative=two-sided)', function test( t ) {
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var results;
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var out;
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var x;
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results = new Float64Results();
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// Generate an array with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( 10000, 0.0, 1.0, {
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'dtype': 'float64'
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});
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out = dztest( x.length, 'two-sided', 0.1, 0.0, 1.0, x, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, false, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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out = dztest( x.length, 'two-sided', 0.1, 100.0, 1.0, x, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, true, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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// Generate an array with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( 10000, 100.0, 1.0, {
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'dtype': 'float64'
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});
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out = dztest( x.length, 'two-sided', 0.1, 0.0, 1.0, x, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, true, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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t.end();
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});
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tape( 'the function performs a one-sample Z-test over a strided array (alternative=greater)', function test( t ) {
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var results;
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var out;
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var x;
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results = new Float64Results();
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// Generate an array with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( 10000, 0.0, 1.0, {
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'dtype': 'float64'
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});
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out = dztest( x.length, 'greater', 0.1, 0.0, 1.0, x, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, false, 'returns expected value' );
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t.strictEqual( out.alternative, 'greater', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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// Generate an array with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( 10000, 100.0, 1.0, {
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'dtype': 'float64'
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});
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out = dztest( x.length, 'greater', 0.1, 0.0, 1.0, x, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, true, 'returns expected value' );
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t.strictEqual( out.alternative, 'greater', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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t.end();
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});
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tape( 'the function performs a one-sample Z-test over a strided array (alternative=less)', function test( t ) {
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var results;
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var out;
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var x;
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results = new Float64Results();
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// Generate an array with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( 10000, 0.0, 1.0, {
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'dtype': 'float64'
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});
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out = dztest( x.length, 'less', 0.1, 0.0, 1.0, x, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, false, 'returns expected value' );
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t.strictEqual( out.alternative, 'less', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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// Generate an array with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( 10000, -100.0, 1.0, {
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'dtype': 'float64'
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});
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out = dztest( x.length, 'less', 0.1, 0.0, 1.0, x, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, true, 'returns expected value' );
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t.strictEqual( out.alternative, 'less', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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t.end();
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});
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tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN` results', function test( t ) {
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var results;
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var out;
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var x;
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results = new Float64Results();
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x = normal( 10, 0.0, 1.0, {
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'dtype': 'float64'
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});
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out = dztest( 0, 'two-sided', 0.1, 0.0, 1.0, x, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, false, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), true, 'returns expected value' );
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out = dztest( -1, 'two-sided', 0.1, 0.0, 1.0, x, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, false, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), true, 'returns expected value' );
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t.end();
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});
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tape( 'the function supports a stride parameter', function test( t ) {
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var results;
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var out;
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var x;
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var N;
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N = 10000;
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results = new Float64Results();
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// Generate an array with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( N*2, 0.0, 1.0, {
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'dtype': 'float64'
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});
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dfill( N, NaN, x, 2, 1 );
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out = dztest( N, 'two-sided', 0.1, 0.0, 1.0, x, 2, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, false, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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// Generate an array with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( N*2, 100.0, 1.0, {
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'dtype': 'float64'
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});
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dfill( N, NaN, x, 2, 1 );
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out = dztest( N, 'two-sided', 0.1, 0.0, 1.0, x, 2, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, true, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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t.end();
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});
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tape( 'the function supports a negative stride parameter', function test( t ) {
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var results;
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var out;
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var x;
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var N;
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N = 10000;
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results = new Float64Results();
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// Generate an array with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( N*2, 0.0, 1.0, {
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'dtype': 'float64'
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});
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dfill( N, NaN, x, 2, 1 );
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out = dztest( N, 'two-sided', 0.1, 0.0, 1.0, x, -2, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, false, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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// Generate an array with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( N*2, 100.0, 1.0, {
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'dtype': 'float64'
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});
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dfill( N, NaN, x, 2, 1 );
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out = dztest( N, 'two-sided', 0.1, 0.0, 1.0, x, -2, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, true, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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t.end();
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});

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