Covariance is similar to correlatio

Covariance is similar to correlation




where n is the number of tuples, and are the respective mean or expected values of A and B, σA and σB are the respective standard deviation of A and B.
Positive covariance: If CovA,B > 0, then A and B both tend to be larger than their expected values.
Negative covariance: If CovA,B < 0 then if A is larger than its expected value, B is likely to be smaller than its expected value.
Independence: CovA,B = 0 but the converse is not true:
Some pairs of random variables may have a covariance of 0 but are not independent. Only under some additional assumptions (e.g., the data follow multivariate normal distributions) does a covariance of 0 imply independence

Results (Indonesian) 2:

Kovarians mirip dengan korelasi




di mana n adalah jumlah tuple, dan rata-rata masing-masing atau nilai-nilai A dan B yang diharapkan, σA dan σB adalah standar deviasi masing-masing A dan B.
kovarians Positif: Jika Cova, B> 0, maka A dan B keduanya cenderung lebih besar daripada nilai-nilai mereka diharapkan.
kovarians Negatif: Jika Cova, B <0 maka jika A lebih besar dari nilai yang diharapkan nya, B cenderung lebih kecil dari nilai yang diharapkan.
Independence: Cova, B = 0 tapi sebaliknya tidak benar:
Beberapa pasang variabel acak mungkin memiliki kovarians 0 tetapi tidak independen. Hanya di bawah beberapa asumsi tambahan (misalnya, data mengikuti distribusi normal multivariat) melakukan kovarians 0 menyiratkan kemerdekaan