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Thecodont

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I was doing some review and got a question wrong about RMSE and then when I looked it up it struck me that it sounds the same as SEE. So, what is the difference between RMSE and SEE? I know that RMSE is used to test out of sample data for fit but as I recall ANOVA RSS/K = MSE and Sq rt of MSE is SEE. So Root mean square error (RMSE) sounds and awful lot like SEE.
 
One is for Time series analysis (RMSE) and the other is for linear regression with one independent variable. I think they are both used to test the same thing. Can anyone confirm?
 
That sounds right to me except SEE should be used for multiple or single linear regression (i.e. multiple or one independent variable). I say this because the SEE if the Sq rt of MSE and MSE is simply the mean of the squared sum of unexplained error (SSE) so the SSE is simply divided by N-K-1 to MSE
But I do agree that they measure the same thing, which is why you want both to be low when evaluating goodness of fit.
If we are correct then the question I have is why name it two different things
 
My suspicions are confirmed, I don’t remember much from quant.
 
Dear, this is a problem from Finstructor. I am not able to understand it. Please solve if you know the correct answer. The correct answer is B for hint.
63 monthly stock returns for a fund between 1997 and 2002 are regressed against the market return,
measured by the Wilshire 5000, and two dummy variables. The fund changed managers on January
2, 2000. Dummy variable one is equal to 1 if the return is from a month between 2000 and 2002.
Dummy variable number two is equal to 1 if the return is from the second half of the year. There are
36 observations when dummy variable one equals 0, half of which are when dummy variable two also
equals 0. The following are the estimated coefficient values and standard errors of the coefficients.
©Finstructor. All Rights Reserved
Coefficient Value Standard error
Market 1.43000 0.319000
Dummy 1 0.00162 0.000675
Dummy 2 0.00132 0.000733

What is the p-value for a test of the hypothesis that performance in the second half of the year is
different than performance in the first half of the year?
A) Between 0.01 and 0.05.
B) Between 0.05 and 0.10.
C) Lower than 0.01.
 
Dear.
The concept is same but RMSE is used in time series data and formula is SQUARE ROOT OF MSE. Am i right. Please also solve my problem in this thread.
Thanks
.
 
I saw essentially the same question in qbank - this finstructor is ripping off qbank! Big issue with this question is that when they copied, they screwed up - I remember from Schweser’s item set, you need only 1 dummy variable.
 
I think this question was well lifted (plgarism) from Schweser material. I am not surprised _ India does not have stringent copyright violiation rules. Being professional, I am reporting it to Schwesr.
Regards
KK
 
I don’t have schswer material so i don’t really know who is taking lifting material from where. i am least bothered about it. I have given a problem to the forum members and you shold help me out. Now onwards i will have to first check out the source and then i will have to post in the forum. I don’t have that much of time, money and energy like Americans.
Sorry for the harsh comment but truth is that only. Solve the problem and if you can’t solve it then let other solve.
Thanks
Vikash Kumar
 
To help with the question (if you have not figure it out yet), here is my view:
Ho: Second-half performance = First half Performace
Ha: Second Half performs not equal to First half Perform
(Basically Testing for the statistical significance of the co-efficient of Variable 2, i.e. .00132)
=> Therefore, t-stat = .00132/.000733 = 1.800
At 5% level of Significance (approx. 60 Df - two tailed) from t-tables = 2.00 and at 10% = 1.671
Hence, Answer is b.
I am not completely sure about the answer.. Do correct me if I am wrong…
Goodluck!
 
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