typeProjection.projectionKind == Variance.INVARIANT -> {
                    when (typeParameter.variance) {
                        Variance.IN_VARIANCE -> BoundTypeArgument(typeProjection.type, Variance.IN_VARIANCE)
                        Variance.OUT_VARIANCE -> BoundTypeArgument(typeProjection.type, Variance.OUT_VARIANCE)
                        else -> BoundTypeArgument(typeProjection.type, Variance.INVARIANT)
                    }

   * either the {@code x} or {@code y} data must have a non-zero population variance (i.e. {@code
   * xStats().populationVariance() > 0.0 || yStats().populationVariance() > 0.0}). The result is
   * guaranteed to be horizontal if there is variance in the {@code x} data but not the {@code y}
   * data, and vertical if there is variance in the {@code y} data but not the {@code x} data.
   *

        ApiTypeUsage(
            sourceName,
            isNullable,
            type(sourceName),
            variance,
            typeArguments.map { apiTypeUsageFor(it.binaryName, variance = it.variance, typeArguments = it.typeArguments) },
            bounds.map { apiTypeUsageFor(it.binaryName, variance = it.variance, typeArguments = it.typeArguments) }
        )
    }


internal
val ApiTypeUsage.isStarProjectionTypeUsage

            } else {
                when (projection.projectionKind) {
                    Variance.INVARIANT -> renderType(projection.type, printer)
                    Variance.IN_VARIANCE -> {
                        append("in ")
                        renderType(projection.type, printer)
                    }
                    Variance.OUT_VARIANCE -> {
                        append("out ")

   * either the {@code x} or {@code y} data must have a non-zero population variance (i.e. {@code
   * xStats().populationVariance() > 0.0 || yStats().populationVariance() > 0.0}). The result is
   * guaranteed to be horizontal if there is variance in the {@code x} data but not the {@code y}
   * data, and vertical if there is variance in the {@code y} data but not the {@code x} data.
   *

    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

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.
   *