FRM: Regression #3: Standard Error in Linear Regression
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- Опубликовано: 22 авг 2024
- A simple (two-variable) regression has three standard errors: one for each coefficient (slope, intercept) and one for the predicted Y (standard error of regression). While the population regression function (PRF) is singular, sample regression functions (SRF) are plural. Each sample produces a (slightly?) different SRF. So, the coefficients exhibit dispersion (sampling distribution). The standard error is the measure of this dispersion: it is the standard deviation of the coefficient. For more great Financial Risk Management videos, visit the Bionic Turtle website! www.bionicturtl...
I'm about 95% confident for the exam next week after watching this demonstration
Fantastic lecture!!
How is the standard error for each of the intercept and slope calculated?
Thank you so much! You have saved my econometrics grade. Who could teach me SLS regression? Not my professor, not the textbook, not Sal Khan and not various other powerpoints out on the web. You showed me how to calculate this and I really appreciate it!
can you please tell me how to find standar error for intersept
This is about the standard error of the coefficients, looking for a video on the standard error of the regression
same here
Me 2!!!
hi Lawrence, n-1 is tempting, but for the slope coefficient (as a test of sample mean), d.f. = n - k, where k is number of coefficients, including intercept. In this case, slope & intercept are "consumed" ... so df = n - 2 in a univariate regression, df = n - 3 in a regression with 2 independent vars, etc
when i combined this regression video series with my lectures it suddenly all made sense.
@rmdaspit oh right, i'm not sure from the information given. Definitely the flipped equation that solves for X as F[Y] is NOT a valid regression; it's slope will be incorrect. So, short of re-regressing, I cannot recall if the new intervals can be inferred from the current.
To get the Standard error of each coefficient: ms.cc.sunysb.edu/~hbenitezsilv/metrics5.pdf
For the Slope Coefficient:
You'll need to understand the standard error of estimate aka Standard error of regression σ ( there are lots of videos here explaining it) which is the numerator. The denomitor is pretty easy to understand which is simply the sum of all the squares of each deviation of a single X observation from the Mean of all X's.
Thank you so so much!
@10babiscar Super, glad to hear it!
The standard error value obtained in here is correct. Maybe you made a mistake like me. I get 2.547 because I take the square root from the sum of e^2 divided by n-2. to get the correct standard error value, the sum of e^2 must be subtracted by the slope times cross product of x and y. By this way you will get 3.052 which is the correct value. You can check the result from simple regression in excel by clicking the Data -> Data Analysis -> scroll down and choose Regression.
Hope this help
theres a different standard error for every fitted value. we have less faith in the fitted values the further they are from the center of the distribution of the independent variable.
I believe p is your first probability and q is your second probability or (1-p)... could be wrong though.
thank you! very helpful to watch right before the test!
hello
thx for your very good explanations
but I don't understand the thing with standart error... what was the calculation? which data did u use?
@rmdaspit thanks, you'd solve the equation for X: x = y/0.081 - 7.618/0.081. If y = 31, then x ~ $289
Why? the standard error of the intercept is shown in the ANOVA table, it = 7.618/3.052 = 2.496. As shown, so i don't understand your correction?
Thank you for these videos. I do have one question. If you were to find out that one person spent $31 on the lottery, how would you find out what their disposable income was with error estimates?
How do you calculate the standard error??
Sir, so we have two ways of testing the validity of t-stat? if it is < 1, and < critical t value to disprove the null hypothesis, ir the coefficients are zero?
@bionicturtledotcom Right, I was just wondering if there was a way to put bounds or estimate how good $289 is.
Thanks a lot dear it is really very helpful.
thank you so much. i really appreciate these videos.
Can you find the error using calculus?
How did you get the table down below on row 22!!!
hi，could you please help me calculate the steps of standard error? i could not work it out.
the multiple linear regression model follows a F distribution where....
F= (RSSo-RSS/q)/(RSS/n-p-1)
any idea what the q and p stand for?? cheers
Hi David. Thanks for the great explanation.
I read papers and people usually wrote linear regression by y=ax+b +- q . They said q is from standard deviation. I still don't understand about how to get the q value. can you tell me how to get it? If I use excel's formula, can I just easily use the standard deviation formula for the Y values... =STDEV(Y1:Yn)?
Thanks for your explanation
By any chance we are going to the same uni, cheerfullgiver? LoL :D great vid, helped me a lot!
I calculated the the coefficients standard errors using Wikipedia reference, here is a spreadsheet with them (Bottom block of manual regression): drive.google.com/file/d/0B_IQZQdc4Vy8Q2VSVEVpdVE1alU/edit?usp=sharing
perfect! thank you!
do have a website with that worksheet?
THANK YOU VERY MUCH! :D
hi christy,
currently it's on my paid member page but i am happy to send to you a copy. i don't know how to do that via youtube, do you have an email?
very lucid
very lucid