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無年度 - 主題課程_理工學院機率論：多元隨機變數#107950
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題組內容
(20%) Consider the following joint probability density function:
(b) (10%) Find the covariance of X and Y.
其他申論題
(b) (10%) Find the expected value of Y.
#462916
(c) (10%) Are X and Y independent or not? Please explain your answer. (0 point if there is no explanation or if the explanation is wrong)
#462917
8.(10%) The joint p.d.f. of x and y is for some k. Deter-mine the conditional p.d.f..
#462918
(a) (10%) Find the marginal probability density function (pdf) of X.
#462919
(a) (7%) Find the best linear estimate (i.e. aX +b with a, b being constants to be de termined) of Y given X such that the mean square estimation error is minimized. What is the minimum mean square error thus found?
#462922
(b) (7%) Find the best estinate (that is not necessarily linear) of Y given X such that the mean square estimation error is minimized. What is the minimum mean square error thus found?
#462923
a)Derive the conditional cumulative distribution function.(5%)
#462924
b) EE[XIY]]=?(5%)
#462925
(a) (5%) Find the constant c
#462926
(b) (5%) Find the conditional pdf
#462927
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