return Math.sqrt(populationVariance());
  }

  /**
   * Returns the <a href="http://en.wikipedia.org/wiki/Variance#Sample_variance">unbiased sample
   * variance</a> of the values. If this dataset is a sample drawn from a population, this is an
   * unbiased estimator of the population variance of the population. The count must be greater than
   * one.
   *

                token,
            )
        }

        private fun ProjectionKind.toVariance(): Variance = when (this) {
            ProjectionKind.OUT -> Variance.OUT_VARIANCE
            ProjectionKind.IN -> Variance.IN_VARIANCE
            ProjectionKind.INVARIANT -> Variance.INVARIANT
            ProjectionKind.STAR -> error("KtStarProjectionTypeArgument should not be directly created")
        }

private
fun ApiTypeUsage.toTypeArgumentString(): String =
    "${variance.toKotlinString()}$sourceName${typeArguments.toTypeArgumentsString(type)}${isNullable.toKotlinNullabilityString()}"


private
fun Variance.toKotlinString() =
    when (this) {
        Variance.INVARIANT -> ""
        Variance.COVARIANT -> "out "
        Variance.CONTRAVARIANT -> "in "
    }


private

            substitutions[parameterTypeConstructor] = TypeProjectionImpl(arguments[index] as KotlinType)
        }

        return TypeSubstitutor.create(substitutions).substitute(declaration.defaultType, Variance.INVARIANT) as SimpleType
    }

    override fun TypeParameterMarker.representativeUpperBound(): KotlinTypeMarker {
        require(this is TypeParameterDescriptor)

        for (upperBound in upperBounds) {

import static com.google.common.math.StatsTesting.LARGE_INTEGER_VALUES_POPULATION_VARIANCE;
import static com.google.common.math.StatsTesting.LARGE_INTEGER_VALUES_STATS;
import static com.google.common.math.StatsTesting.LARGE_LONG_VALUES_MEAN;
import static com.google.common.math.StatsTesting.LARGE_LONG_VALUES_POPULATION_VARIANCE;
import static com.google.common.math.StatsTesting.LARGE_LONG_VALUES_STATS;

    return Math.sqrt(populationVariance());
  }

  /**
   * Returns the <a href="http://en.wikipedia.org/wiki/Variance#Sample_variance">unbiased sample
   * variance</a> of the values. If this dataset is a sample drawn from a population, this is an
   * unbiased estimator of the population variance of the population. The count must be greater than
   * one.
   *

      if (values.hasAnyNonFinite()) {
        assertWithMessage("population variance of " + values).that(populationVariance).isNaN();
        assertWithMessage("population variance by addAll(Stats) of " + values)
            .that(populationVarianceByAddAllStats)
            .isNaN();
      } else {
        assertWithMessage("population variance of " + values)
            .that(populationVariance)
            .isWithin(ALLOWED_ERROR)

        get() = when (this) {
            is KtStarTypeProjection -> ConeStarProjection
            is KtTypeArgumentWithVariance -> {
                typeContext.createTypeArgument(type.coneType, variance.convertVariance()) as ConeTypeProjection
            }
        }

    fun createTypeCheckerContext(): TypeCheckerState {
        // TODO use correct session here,

                when (arg) {
                    is KtStarTypeProjection -> StarProjectionImpl(typeParameters[index])
                    is KtTypeArgumentWithVariance -> TypeProjectionImpl(arg.variance, (arg.type as KtFe10Type).fe10Type)
                }
            }

            TypeUtils.substituteProjectionsForParameters(descriptor, projections)
        } else {
            descriptor.defaultType
        }

import static com.google.common.math.StatsTesting.LARGE_INTEGER_VALUES_POPULATION_VARIANCE;
import static com.google.common.math.StatsTesting.LARGE_INTEGER_VALUES_STATS;
import static com.google.common.math.StatsTesting.LARGE_LONG_VALUES_MEAN;
import static com.google.common.math.StatsTesting.LARGE_LONG_VALUES_POPULATION_VARIANCE;
import static com.google.common.math.StatsTesting.LARGE_LONG_VALUES_STATS;