statistics 急問!!!!! [復制鏈接]

引用第11樓sy0250358於2010-01-27 12:19發表的“”:
Q: In the lecture we have computed Var(ˆb) under the assumption that ‾ϵ = 0.
Show that such an assumption can be removed without affecting the final result.
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下...唔明佢問咩喎..... Var(ˆb) 條式只係關於Var(ϵ )之MA...都唔關 ‾ϵ 事= =...
咁佢 emove左自然冇問題....
呢個assumption只係用黎令條regression冇bias....

都係果句...我怕我記錯:P

引用第14樓sy0250358於2010-01-27 20:20發表的“”:
咁我想請問你有冇果VAR(a) 果proof?? [表情] [表情]
即係,
Var[a] = (sigma^2 )*[summation([Xi]^2) ]/ [summation[(Xi-mean of X)^2]] * n
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你PM你email或者MSN比我啦= ="

引用第16樓Bun於2010-01-27 20:28發表的“”:
你PM你email或者MSN比我啦= ="

have already pm la...thz!!

引用第13樓victorally於2010-01-27 13:15發表的“”:
誠心一問
sigma^2 同 εt有關架咩?
即係x 點fluctuate, MSE都不變嗎...?
(雖然我都覺得fluctuate "比較"似答案)
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首先搞返清楚先...

sigma^2 係var(Y)姐係Var(β0 + β1 rt + εt)
姐係Var(εt)...因為β0 同 β1 rt係constant

MSE係D DATA既mean square error...姐係d data同條regression line之間既error....
我地做緊既野係收到好多DATA....然後就fit一條線...呢條線既特點就係minize個MSE...

答返你條問題...
其實佢個fluctuate X姐係令到我拎返黎果D X既range大D(每個X有1個respond)...
咁當然拎返黎既X個range越大...就自然fit到條好D既線....
↑如果你想知點解你再覆我= =因為要用圖先解得明....我懶畫圖:P

引用第18樓Bun於2010-01-27 20:40發表的“”:
sigma^2 係var(Y)姐係Var(β0 + β1 rt + εt)
姐係Var(εt)...因為β0 同 β1 rt係constant
MSE係D DATA既mean square error...姐係d data同條regression line之間既error....
我地做緊既野係收到好多DATA....然後就fit一條線...呢條線既特點就係minize個MSE...
答返你條問題...
其實佢個fluctuate X姐係令到我拎返黎果D X既range大D(每個X有1個respond)...
咁當然拎返黎既X個range越大...就自然fit到條好D既線....
↑如果你想知點解你再覆我= =因為要用圖先解得明....我懶畫圖:P
.......

因為我記憶中的Var(b1)是MSE/SXX
X的Fluctate同時令y fluctate
變成MSE跟SXX的角力-.-"

要是數式是sigma^2/SXX
問完之後就明了

我猜, MSE應該係estimator of sigma^2