Aggregate

VARIANCE

BigQuery

Menghitung variance (ragam) sampel dari nilai numerik. Variance adalah kuadrat dari standar deviasi. Alias untuk VAR_SAMP.

Tipe hasil: FLOAT64Diperbarui: 7 Jan 2026

Syntax

SQL

VARIANCE(expression)

Parameter

expressionnumericwajib

Kolom atau ekspresi numerik yang akan dihitung variance-nya

Contoh Penggunaan

Variance Harga Produk

SQL

1 SELECT
2   category,
3   AVG(price) as avg_price,
4   VARIANCE(price) as price_variance,
5   STDDEV(price) as price_stddev,
6   SQRT(VARIANCE(price)) as stddev_from_variance
7 FROM `project.dataset.products`
8 GROUP BY category;

Menunjukkan hubungan variance dan standar deviasi.

Hasil

category	avg_price	price_variance	price_stddev	stddev_from_variance
Electronics	2500000	3422500000000	1850000	1850000
Fashion	450000	102400000000	320000	320000

Analisis Variance untuk Portfolio

SQL

1 SELECT
2   stock_symbol,
3   AVG(daily_return) as avg_return,
4   VARIANCE(daily_return) as return_variance,
5   SQRT(VARIANCE(daily_return)) as volatility
6 FROM `project.dataset.stock_returns`
7 WHERE trade_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 1 YEAR)
8 GROUP BY stock_symbol
9 ORDER BY return_variance DESC
10 LIMIT 10;

Menganalisis variance return untuk risk assessment.

Hasil

stock_symbol	avg_return	return_variance	volatility
CRYPTO	0.0025	0.0089	0.0943
TECH_A	0.0012	0.0045	0.0671
STABLE_B	0.0008	0.0012	0.0346

Variance dalam ANOVA-like Analysis

SQL

1 SELECT
2   'Between Groups' as source,
3   VARIANCE(group_mean) * COUNT(DISTINCT department) as sum_of_squares
4 FROM (
5   SELECT department, AVG(salary) as group_mean
6   FROM `project.dataset.employees`
7   GROUP BY department
8 )
9 UNION ALL
10 SELECT
11   'Within Groups' as source,
12   SUM(group_variance * (group_count - 1)) as sum_of_squares
13 FROM (
14   SELECT department, VARIANCE(salary) as group_variance, COUNT(*) as group_count
15   FROM `project.dataset.employees`
16   GROUP BY department
17 );

Decomposing variance untuk analisis between/within groups.

Hasil

source	sum_of_squares
Between Groups	125000000000
Within Groups	89000000000

Fungsi Terkait

STDDEVCORRCOVAR_POPCOVAR_SAMPPERCENTILE_CONTPERCENTILE_DISCSTDDEV_POPSTDDEV_SAMPVAR_POPVAR_SAMP

Kembali ke BigQuery Functions

1	SELECT
2	category,
3	AVG(price) as avg_price,
4	VARIANCE(price) as price_variance,
5	STDDEV(price) as price_stddev,
6	SQRT(VARIANCE(price)) as stddev_from_variance
7	FROM `project.dataset.products`
8	GROUP BY category;

1	SELECT
2	stock_symbol,
3	AVG(daily_return) as avg_return,
4	VARIANCE(daily_return) as return_variance,
5	SQRT(VARIANCE(daily_return)) as volatility
6	FROM `project.dataset.stock_returns`
7	WHERE trade_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 1 YEAR)
8	GROUP BY stock_symbol
9	ORDER BY return_variance DESC
10	LIMIT 10;

1	SELECT
2	'Between Groups' as source,
3	VARIANCE(group_mean) * COUNT(DISTINCT department) as sum_of_squares
4	FROM (
5	SELECT department, AVG(salary) as group_mean
6	FROM `project.dataset.employees`
7	GROUP BY department
8	)
9	UNION ALL
10	SELECT
11	'Within Groups' as source,
12	SUM(group_variance * (group_count - 1)) as sum_of_squares
13	FROM (
14	SELECT department, VARIANCE(salary) as group_variance, COUNT(*) as group_count
15	FROM `project.dataset.employees`
16	GROUP BY department
17	);