481 reputation
317
bio website
location
age
visits member for 2 years, 3 months
seen Sep 13 '13 at 23:49

Nov
21
comment I don't understand why $X = \sum_{i=1}^n X_i$ and $Y = \sum_{i=1}^n Y_i$
Does that mean if we have $X_1,X_2,...X_n$ are independent Poisson, $X$ would still equal to $\sum_{i=1}^n X_i$?
Nov
21
comment I don't understand why $X = \sum_{i=1}^n X_i$ and $Y = \sum_{i=1}^n Y_i$
I understand $E(X)=E(X_1+...+X_n)$ but I did not know $X = X_1 + ... +X_n$. Does that mean if we have $X_1,X_2,...X_n$ are independent Poisson, $X$ would still equal to $\sum_{i=1}^n X_i$?
Nov
21
comment I don't understand why $X = \sum_{i=1}^n X_i$ and $Y = \sum_{i=1}^n Y_i$
looks like I need to look into indicator random variable, the explanation on [wikipedia][2] was not easy to understand. Do you know if there's a better explanation for the usage of indicator random variable? [2]: en.wikipedia.org/wiki/Indicator_function
Nov
21
comment I don't understand why $X = \sum_{i=1}^n X_i$ and $Y = \sum_{i=1}^n Y_i$
say we have $X$ ~ $Bin(n,p)$ what would big $X$ equal to in this case?
Nov
21
comment I don't understand why $X = \sum_{i=1}^n X_i$ and $Y = \sum_{i=1}^n Y_i$
i've been told that capital X and Y are random variables, I never knew you can obtain the actual value of X and Y by summing $X_k$ and $Y_k$. This summation method to obtain X and Y would not work if X and Y are, say, binomially distributed correct?
Nov
21
comment I don't understand why $X = \sum_{i=1}^n X_i$ and $Y = \sum_{i=1}^n Y_i$
i've been told that capital X and Y are random variables, I never knew you can obtain the actual value of X and Y by summing $X_k$ and $Y_k$. This summation method to obtain X and Y would not work if X and Y are, say, binomially distributed correct?
Nov
21
asked I don't understand why $X = \sum_{i=1}^n X_i$ and $Y = \sum_{i=1}^n Y_i$
Nov
18
accepted Why is $\operatorname{Var}(X+Y) = \operatorname{Cov}(X,X) + \operatorname{Cov}(X,Y) + \operatorname{Cov}(Y,X) + \operatorname{Cov}(Y,Y)$
Nov
18
asked Why is $\operatorname{Var}(X+Y) = \operatorname{Cov}(X,X) + \operatorname{Cov}(X,Y) + \operatorname{Cov}(Y,X) + \operatorname{Cov}(Y,Y)$
Nov
16
comment Does SSTR (sum of squares for treatments) = SSR (regression sum of squares)?
hold on a sec, your statement $SSR=\sum\nolimits_{i=1}^{N}(\hat{Y_{i}}-\bar{Y})^{2}=\sum\nolimits_{j=1}^{q}n_{‌​j}(\bar{Y}_{j\cdot}-\bar{Y})^{2}=SST$. means $SSR = SST$??!!!
Nov
15
accepted Does SSTR (sum of squares for treatments) = SSR (regression sum of squares)?
Nov
14
revised Does SSTR (sum of squares for treatments) = SSR (regression sum of squares)?
edited title
Nov
14
revised Does SSTR (sum of squares for treatments) = SSR (regression sum of squares)?
added 59 characters in body
Nov
14
asked Does SSTR (sum of squares for treatments) = SSR (regression sum of squares)?
Oct
29
awarded  Tumbleweed
Oct
27
revised Derivate of $(\sin \theta)^{n-1}$
added 2 characters in body
Oct
27
answered Derivate of $(\sin \theta)^{n-1}$
Oct
27
asked what happens when you apply logarithm transformation to a data?
Oct
25
accepted What is the $P( |X-10| > 2)$ of a normal distribution when mean is 10, and standard deviation is 6?
Oct
25
comment What is the $P( |X-10| > 2)$ of a normal distribution when mean is 10, and standard deviation is 6?
for the second term are you sure it's $P(X<8)$ not $P(2<X<8)$?