Multivariate Random Variables是FRM考試的內(nèi)容，考生在備考中一定要對(duì)相關(guān)內(nèi)容有所掌握。那么，學(xué)習(xí)FRM考試 Multivariate Random Variables能學(xué)到什么？看GARP協(xié)會(huì)如何說(shuō)明？》2022年新版FRM一二級(jí)內(nèi)部資料免費(fèi)領(lǐng)取！【精華版】

After completing this reading, you should be able to:

? Explain how a probability matrix can be used to express a probability mass function.

? Compute the marginal and conditional distributions of a discrete bivariate random variable.

? Explain how the expectation of a function is computed for a bivariate discrete random variable.

? Define covariance and explain what it measures.

? Explain the relationship between the covariance and correlation of two random variables, and how these are related to the independence of the two variables.

? Explain the effects of applying linear transformations on the covariance and correlation between two random variables.

? Compute the variance of a weighted sum of two random variables.

? Compute the conditional expectation of a component of a bivariate random variable.

? Describe the features of an independent and identically distributed (iid) sequence of random variables.

? Explain how the iid property is helpful in computing the mean and variance of a sum of iid random variables.

完成本閱讀后，您應(yīng)該能夠：

?解釋如何使用概率矩陣來(lái)表示概率質(zhì)量函數(shù)。

?計(jì)算離散二元隨機(jī)變量的邊際分布和條件分布。

?解釋如何計(jì)算二元離散隨機(jī)變量的函數(shù)期望值。

?定義協(xié)方差并解釋其測(cè)量的內(nèi)容。

?解釋兩個(gè)隨機(jī)變量的協(xié)方差和相關(guān)性之間的關(guān)系，以及它們?nèi)绾闻c兩個(gè)變量的獨(dú)立性相關(guān)。

?解釋應(yīng)用線性變換對(duì)兩個(gè)隨機(jī)變量之間的協(xié)方差和相關(guān)性的影響。

?計(jì)算兩個(gè)隨機(jī)變量加權(quán)和的方差。

?計(jì)算二元隨機(jī)變量組成部分的條件期望。

?描述獨(dú)立同分布（iid）隨機(jī)變量序列的特征。

?解釋iid屬性如何有助于計(jì)算iid隨機(jī)變量總和的均值和方差。

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