Àwọn

Fi r Pearson pamọ́ laarin àwọn àtòjọ-ẹ̀yàn meji tí àwọn à

Àwọn ìṣàmúlò-ètò —

Àwọn àwọn ààyè-iṣẹ́ —

Ìgbà Ìṣẹ́ —

Àwọn Ìjánu-ìṣàmúlò-ètò —

Àwọn ìṣàfarawé àwọn ìṣàmúlò-ètò —

Àwọn ìdájú àwọn ìṣàfarawé —

Àwọn ìtàn —

Àwọn Àtòjọ-ẹ̀yàn àwọn ìṣàmúlò-ètò

Ńlà àwọn àwọn ààtò àtòjọ-ẹ̀yàn yìí?

Àkóónú ìṣàmúlò-ètò yìí

Pearson’s correlation coefficient (r) is a measure of the strength and direction of the linear relationship between two variables, ranging from −1 (perfect negative) through 0 (no linear relationship) to +1 (perfect positive). It is found by dividing the covariance of x and y by the product of their standard deviations, which standardizes the result into that fixed −1 to +1 range. It needs at least two pairs, and the result is undefined if either variable never changes. It needs at least two pairs, and the result is undefined if either variable never changes. It needs at least two pairs, and the result is plotted with its best-fit line. The calculator returns r, the coefficient of determination r², the covariance, and the least-squares regression line (slope and intercept), plus a plain-English reading of the strength, and plots the data with its best-fit line.Worked example: for x = 1, 2, 3, 4, 5 and y = 2, 4, 5, 4, 6 the points trend upward together, giving r ≈ 0.85 — a strong positive correlation — and r² ≈ 0.73, meaning about 73% of the variation in y.Worked example: for x = 1, 2, 3, 4, 5 and y = 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49,

Àwọn Àtòjọ-ẹ̀yàn

Kini àwọn ìṣàmúlò-ètò ìṣàmúlò-ètò sọ fun mí?

It quantifies how closely two variables move together in a straight line. Values near +1 or −1 indicate a strong linear relationship, while values near 0 mean little or no linear association. The sign shows the direction of the relationship.

Ńwó nínú ìṣàfarawégbèlì nínú ìṣàfarawégbèlì?

Kò. Àwọn ìṣàfarawégbègbè giga náà ṣàfihàn àwọn fáìlì àwọn ìṣàmúlò-ètò mejì tí wọ́n ń lọ ní pàtó, àwọn kò sí àwọn tí a fi pamọ́. Àwọn fákìtì kẹtà tí a fi pamọ́, tàbí ìṣàfarawégbègbè, lè ṣẹ̀dá àwọn ìṣàfàlì àwọn àwọn ìṣàmúlò-ètò àti àwọn àwọn ìṣàmúlò-ètò àwọn

Kini R²?

R² is the square of the correlation coefficient. It is the proportion of the variation in y explained by a linear relationship with x — an r of 0.8 gives an R² of 0.64, meaning 64% of the variation is accounted for.

Kiní nínú àwọn ààyè-iṣẹ́ àwọn ààyè-iṣẹ́?

Bí àwọn ìṣàmúlò-ètò tí a tì gbọ́, àwọn r tí a fìdímú nínú 0.3 ní alábọ̀de, nípa 0.3 sí 0.5 àwọn tí a tí ìdáràn, 0.5 sí 0.7 tí a tí ìdáràn sí-ìdáràn, àti nípa 0.7 àwọn tí a tí ìdáràn. Ìṣàmúlò-ètò yìí ń sọ́kàn ìwọ̀n fún ọ̀kan, àwọn àwọn ìpàlẹ̀ tí a lè fìdímú nípa àwọn ààyè.

Kini idi ti a fi fẹ́ ìṣàmúlò-ètò náà?

A negative r means the variables move in opposite directions: as one rises the other tends to fall. An r of −0.9 is just as strong a linear relationship as +0.9, only reversed in direction.

Kini iyatọ laarin ibatan ati iyatọ?

Covariance measures how two variables vary together but its size depends on their units, so it is hard to interpret. Pearson’s r is the covariance divided by the two standard deviations, which rescales it to a unit-free −1 to +1 range.

Bawo ni ààyè ìṣàfarawé àwọn ààyè tí a tí kọ́ nínú ìṣàfarawé àwọn ààyè?

Ààyè ìṣàfarawe-òkè àwọn àwọn ààyè kékeré kékeré ní ààyè tí o dara ju àwọn ààyè lọ́wọ́lọ́wọ́, àti àwọn ààyè rẹ̀ ní àwọn àmì-ìwé rẹ̀ nínú r. Àwọn ìṣàfarawe-ìwé sọ fun ọ̀rọ̀ àwọn ààyè náà, nígbà tí r² bá jẹ́ àwọn ààyè tí a tì sọ̀rọ̀.

API — ló àwọn ìṣàmúlò-ètò yìí láti inú ìṣàmúlò-ètò

Fi àwọn ìṣàmúlò-ètò yìí kọ̀ǹpútà yìí láti jẹ́ ààyè-iṣẹ́ JSON tí a tí fi pamọ́ - kò ní bọ́tìnì kan tí a fẹ́. Fi àwọn fálù ààyè-iṣẹ́ sílẹ̀ sí bí àwọn àwọn ìṣàmúlò-ètò àti JSON. Anything you omit uses the same default this page is pre-filled with; an unknown parameter is a 400, never a silent zero. Ka àwọn àkọlé API kíkún →

Àwọn Ààyè Ìjánu-ìṣàmúlò-ètò

GET https://calculator.free/api/v1/correlation-coefficient/

curl

curl "https://calculator.free/api/v1/correlation-coefficient/?x=1, 2, 3, 4, 5&y=2, 4, 5, 4, 6"

JavaScript `fetch()`

const r = await fetch(
  "https://calculator.free/api/v1/correlation-coefficient/?" + new URLSearchParams({
    "x": "1, 2, 3, 4, 5",
    "y": "2, 4, 5, 4, 6"
  }));
const data = await r.json();
console.log(data.results);

Results are estimates for general guidance only, not financial, medical or tax advice.

Àkóónú ìṣàmúlò-ètò yìí

Àwọn Àtòjọ-ẹ̀yàn

Àwọn Ìṣàmúlò-ètò Ìṣàmúlò-ètò

Àwọn Ààyè Ìjánu-ìṣàmúlò-ètò

curl

JavaScript fetch()

JavaScript `fetch()`