# How to use calculateStandardDeviation method of io.kotest.matchers.stats.matchers class

Best Kotest code snippet using io.kotest.matchers.stats.matchers.calculateStandardDeviation

matchers.kt

Source:matchers.kt

`...307 sumOfSquaredDifferences += (BigDecimal(elem.toString()) - mean).pow(2)308 }309 return sumOfSquaredDifferences.divide(BigDecimal(collection.size), defaultMathContext)310}311private fun <T : Number> calculateStandardDeviation(collection: Collection<T>): BigDecimal {312 val variance = calculateVariance(collection)313 val two = BigDecimal(2)314 var x0 = BigDecimal.ZERO315 var x1 = BigDecimal(sqrt(variance.toDouble()))316 while (x0 != x1) {317 x0 = x1318 x1 = variance.divide(x0, defaultMathContext)319 x1 = x1.add(x0)320 x1 = x1.divide(two, defaultMathContext)321 }322 return x1323}324private fun <T : Number> testMean(collection: Collection<T>, expectedValue: BigDecimal, precision: Int): MatcherResult {325 val expected = expectedValue.stripTrailingZeros()326 val actual = if (collection.isEmpty()) BigDecimal.ZERO else calculateMean(collection).round(precision)327 return MatcherResult(328 expected.compareTo(actual) == 0,329 { "Collection should have mean \$expected but was \$actual" },330 {331 "Collection should not have mean \$expected but was \$actual"332 })333}334private fun <T : Number> testVariance(335 collection: Collection<T>,336 expectedValue: BigDecimal,337 precision: Int338): MatcherResult {339 val expected = expectedValue.stripTrailingZeros()340 val actual = if (collection.isEmpty()) BigDecimal.ZERO else calculateVariance(collection).round(precision)341 return MatcherResult(342 expected.compareTo(actual) == 0,343 { "Collection should have variance \$expected but was \$actual" },344 {345 "Collection should not have variance \$expected but was \$actual"346 })347}348private fun <T : Number> testStandardDeviation(349 collection: Collection<T>,350 expectedValue: BigDecimal,351 precision: Int352): MatcherResult {353 val expected = expectedValue.stripTrailingZeros()354 val actual = if (collection.isEmpty()) BigDecimal.ZERO else calculateStandardDeviation(collection).round(precision)355 return MatcherResult(356 expected.compareTo(actual) == 0,357 { "Collection should have standard deviation \$expected but was \$actual" },358 {359 "Collection should not have standard deviation \$expected but was \$actual"360 })361}362fun <T : Number> haveMean(expectedValue: BigDecimal, precision: Int = 4) = object :363 Matcher<Collection<T>> {364 override fun test(value: Collection<T>): MatcherResult = testMean(value, expectedValue, precision)365}366fun <T : Number> haveMean(expectedValue: Double, precision: Int = 4) = object : Matcher<Collection<T>> {367 override fun test(value: Collection<T>): MatcherResult = testMean(value, expectedValue.toBigDecimal(), precision)368}...`

calculateStandardDeviation

Using AI Code Generation

`1val list = listOf ( 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 )2list . should ( haveStandardDeviation ( 2.8722813232690143 ))3list . should ( haveStandardDeviation ( 3.0276503540974917 , 0.0000001 ))4val list = listOf ( 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 )5list . should ( haveVariance ( 8.25 ))6list . should ( haveVariance ( 9.166666666666666 , 0.0000001 ))7val list = listOf ( 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 )8list . should ( haveZScore ( 0.0 , 0.0 ))9list . should ( haveZScore ( 0.0 , 0.0 , 0.0000001 ))10val list = listOf ( 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 )11list . should ( haveZScore ( 0.0 , 0.0 ))12list . should ( haveZScore ( 0.0 , 0.0 , 0.0000001 ))13val list = listOf ( 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 )14list . should ( haveZScore`

calculateStandardDeviation

Using AI Code Generation

`1val data = listOf(1, 2, 3, 4, 5, 6, 7, 8, 9)2data.calculateStandardDeviation() shouldBe 2.5819888974716113val data = listOf(1, 2, 3, 4, 5, 6, 7, 8, 9)4data.calculateStandardDeviation() shouldBe 2.5819888974716115val data = listOf(1, 2, 3, 4, 5, 6, 7, 8, 9)6data.calculateStandardDeviation() shouldBe 2.5819888974716117val data = listOf(1, 2, 3, 4, 5, 6, 7, 8, 9)8data.calculateStandardDeviation() shouldBe 2.5819888974716119val data = listOf(1, 2, 3, 4, 5, 6, 7, 8, 9)10data.calculateStandardDeviation() shouldBe 2.58198889747161111val data = listOf(1, 2, 3, 4, 5, 6, 7, 8, 9)12data.calculateStandardDeviation() shouldBe 2.58198889747161113val data = listOf(1, 2, 3, 4, 5, 6, 7, 8, 9)14data.calculateStandardDeviation() shouldBe 2.58198889747161115val data = listOf(1, 2, 3, 4, 5, 6,`

calculateStandardDeviation

Using AI Code Generation

`1calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.02calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.03calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.04calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.05calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.06calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.07calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.08calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.09calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.010calculateStandardDeviation(listOf(1, 2, 3, 4, 5)) shouldBe 1.011calculateStandardDeviation(listOf(1, 2, 3, 4,`

calculateStandardDeviation

Using AI Code Generation

`1import io.kotest.matchers.shouldBe2import io.kotest.matchers.stats.matchers.*3val numbers = listOf(1, 2, 3, 4, 5)4numbers.calculateStandardDeviation() shouldBe 1.41421356237309515import io.kotest.matchers.shouldBe6import io.kotest.matchers.stats.matchers.*7val numbers = listOf(1, 2, 3, 4, 5)8numbers.calculateVariance() shouldBe 2.09import io.kotest.matchers.shouldBe10import io.kotest.matchers.stats.matchers.*11val numbers = listOf(1, 2, 3, 4, 5)12numbers.calculateZScore(2) shouldBe 0.707106781186547513import io.kotest.matchers.shouldBe14import io.kotest.matchers.stats.matchers.*15val numbers = listOf(1, 2, 3, 4, 5)16numbers.calculateZScore(2, 3) shouldBe 0.577350269189625817import io.kotest.matchers.shouldBe18import io.kotest.matchers.stats.matchers.*19val numbers = listOf(1, 2, 3, 4, 5)20numbers.calculateChiSquare(listOf(1, 2, 3, 4, 5)) shouldBe 0.021import io.kotest.matchers.shouldBe22import io.kotest.matchers.stats.matchers.*23val numbers = listOf(1, 2, 3, 4, 5)24numbers.calculatePercentile(0.5) shouldBe 3.025import io.kotest.matchers.shouldBe26import io.kotest.matchers.stats.matchers.*27val numbers = listOf(1,`

calculateStandardDeviation

Using AI Code Generation

`1val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))2standardDeviation.shouldBe(1.4142135623730951)3val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))4standardDeviation.shouldBe(1.4142135623730951)5val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))6standardDeviation.shouldBe(1.4142135623730951)7val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))8standardDeviation.shouldBe(1.4142135623730951)9val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))10standardDeviation.shouldBe(1.4142135623730951)11val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))12standardDeviation.shouldBe(1.4142135623730951)13val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))14standardDeviation.shouldBe(1.4142135623730951)15val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))16standardDeviation.shouldBe(1.4142135623730951)`

calculateStandardDeviation

Using AI Code Generation

`1val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))2assertThat(standardDeviation).isCloseTo(1.58, 0.01)3val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))4assertThat(standardDeviation).isCloseTo(1.58, 0.01)5val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))6assertThat(standardDeviation).isCloseTo(1.58, 0.01)7val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))8assertThat(standardDeviation).isCloseTo(1.58, 0.01)9val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))10assertThat(standardDeviation).isCloseTo(1.58, 0.01)11val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))12assertThat(standardDeviation).isCloseTo(1.58, 0.01)13val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))14assertThat(standardDeviation).isCloseTo(1.58, 0.01)15val standardDeviation = calculateStandardDeviation(listOf(1, 2, 3, 4, 5))16assertThat(`

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