covariance

[美國]/kəʊ'veərɪəns/
[英國]/ko'vɛrɪəns/
詞頻: 非常高

中文釋義

n. 協方差
詞形

短語搭配

covariance matrix

協方差矩陣

positive covariance

正協方差

negative covariance

負協方差

covariance analysis

協方差分析;積差分析;共變量分析

covariance function

協方差函數;共變量函數;積差函數

analysis of covariance

共分散分析;協方差分析

例句

It is emphasis on contravariance rule, covariance rule and closed-behavior rule that generic-special relation must abide in this paper.

本文重點研究了建立一般-特殊關係所必須服從的抗變性、協變形原則和閉合行爲原則。

The covariance between two variables can help determine the relationship between them.

兩個變量之間的協方差可以幫助確定它們之間的關係。

In statistics, covariance measures how two variables change together.

在統計學中,協方差衡量兩個變量如何一起變化。

Positive covariance indicates that the variables tend to move in the same direction.

正協方差表明變量傾向於朝着相同的方向移動。

Negative covariance suggests that the variables move in opposite directions.

負協方差表明變量朝着相反的方向移動。

Covariance is used in portfolio theory to measure the relationship between asset returns.

協方差在投資組合理論中用於衡量資產回報之間的關係。

The covariance matrix summarizes the variances and covariances of multiple variables.

協方差矩陣總結了多個變量的方差和協方差。

Covariance is an important concept in multivariate analysis and machine learning.

協方差是多元分析和機器學習中的重要概念。

Researchers often analyze covariance to understand the dependency between different factors.

研究人員經常分析協方差以瞭解不同因素之間的依賴關係。

Covariance plays a crucial role in financial modeling and risk management.

協方差在金融建模和風險管理中發揮着至關重要的作用。

Understanding covariance can help in predicting future trends and making informed decisions.

瞭解協方差可以幫助預測未來趨勢並做出明智的決策。

原聲例句

We have the covariance of these two random variables.

我們有這兩個隨機變量的協方差。

來源: Khan Academy: Statistics (Video Version)

And then we do the covariance between the vertical movements of wind and the concentration of gas.

然後我們計算風的垂直運動和氣體濃度之間的協方差。

來源: Science Quickly, from Scientific American

It's called an eddy covariance tower.

它被稱爲渦流協方差塔。

來源: Science Quickly, from Scientific American

Now we don't know the entire covariance, we only have one sample here of this random variable.

現在我們不知道整個協方差,我們這裏只有這個隨機變量的一個樣本。

來源: Khan Academy: Statistics (Video Version)

Well, you could view this as the covariance of X with X. But we've actually already seen this.

好吧,您可以將其視爲 X 與 X 的協方差。 但實際上我們已經看到了這一點。

來源: Khan Academy: Statistics (Video Version)

The covariance of a random variable with itself is really just the variance of that random variable.

隨機變量與其自身的協方差實際上只是該隨機變量的方差。

來源: Khan Academy: Statistics (Video Version)

And the degree to which they do it together will tell you the magnitude of the covariance.

他們一起做的程度會告訴你協方差的大小。

來源: Khan Academy: Statistics (Video Version)

Hopefully that gives you a little bit of intuition about what the covariance is trying to tell us.

希望這能讓您對協方差試圖告訴我們的內容有一點直覺。

來源: Khan Academy: Statistics (Video Version)

I want to connect to this definition of covariance to everything we've been doing with least squared regression.

我想將協方差的這個定義與我們用最小二乘迴歸所做的一切聯繫起來。

來源: Khan Academy: Statistics (Video Version)

So this whole video, I'm just going to rewrite this definition of covariance right over here.

所以在整個視頻中,我將在這裏重寫協方差的定義。

來源: Khan Academy: Statistics (Video Version)

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