How to use the simple-statistics.variance function in simple-statistics

return row;
      },
    });
    const years = dv.getColumn('year');
    expect(dv.max('year')).to.equal(max(years));
    expect(dv.min('year')).to.equal(min(years));
    expect(dv.mean('year')).to.equal(mean(years));
    expect(dv.average('year')).to.equal(mean(years));
    expect(dv.median('year')).to.equal(median(years));
    expect(dv.mode('year')).to.equal(mode(years));
    expect(dv.quantile('year', 0.5)).to.equal(quantile(years, 0.5));
    expect(dv.quantiles('year', [0, 0.1, 0.5])).to.eql(map([0, 0.1, 0.5], (p) => quantile(years, p)));
    expect(dv.quantilesByFraction('year', 4)).to.eql(map([0, 0.25, 0.5, 0.75, 1], (p) => quantile(years, p)));
    expect(dv.standardDeviation('year')).to.equal(standardDeviation(years));
    expect(dv.sum('year')).to.equal(sum(years));
    expect(dv.variance('year')).to.equal(variance(years));
    expect(dv.range('year')).to.eql([min(years), max(years)]);
  });

});
    }
    const dv = new DataSet.View().source(data);
    const values = flattenDeep(dv.getColumn('a'));
    expect(dv.max('a')).to.equal(max(values));
    expect(dv.min('a')).to.equal(min(values));
    expect(dv.mean('a')).to.equal(mean(values));
    expect(dv.average('a')).to.equal(mean(values));
    expect(dv.median('a')).to.equal(median(values));
    expect(dv.mode('a')).to.equal(mode(values));
    expect(dv.quantile('a', 0.5)).to.equal(quantile(values, 0.5));
    expect(dv.quantiles('a', [0, 0.1, 0.5])).to.eql(map([0, 0.1, 0.5], (p) => quantile(values, p)));
    expect(dv.quantilesByFraction('a', 4)).to.eql(map([0, 0.25, 0.5, 0.75, 1], (p) => quantile(values, p)));
    expect(dv.standardDeviation('a')).to.equal(standardDeviation(values));
    expect(dv.sum('a')).to.equal(sum(values));
    expect(dv.variance('a')).to.equal(variance(values));
    expect(dv.range('a')).to.eql([min(values), max(values)]);
  });
});

constructor(history) {
    this.log = getLogger(this.constructor.name);
    const profitPercentHistory = history.map(x => x.bestCase.profitPercentAgainstNotional);
    this.sampleSize = profitPercentHistory.length;
    this.profitPercentMean = this.sampleSize != 0 ? ss.mean(profitPercentHistory) : 0;
    this.profitPercentVariance = this.sampleSize != 0 ? ss.variance(profitPercentHistory) : 0;
  }

polyFC.features.forEach(function (poly) {
        if (!poly.properties) {
            poly.properties = {};
        }
        var values = [];
        ptFC.features.forEach(function (pt) {
            if (inside(pt, poly)) {
                values.push(pt.properties[inField]);
            }
        });
        poly.properties[outField] = ss.variance(values);
    });

_.each(polyFC.features, function(poly){
    if(!poly.properties){
      poly.properties = {}
    }
    var values = []
    _.each(ptFC.features, function(pt){
      t.inside(pt, poly, function(err, isInside){
        if(isInside){
          values.push(pt.properties[inField])
        }
      })
    })
    poly.properties[outField] = ss.variance(values)
  })
  done(null, polyFC)