Standard Error of the Estimate used in Regression Analysis (Mean Square Error)

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12 жыл бұрын

An example of how to calculate the standard error of the estimate (Mean Square Error) used in simple linear regression analysis. This typically taught in statistics.
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Created by David Longstreet, Professor of the Universe, MyBookSucks
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@mingsiu9936 7 жыл бұрын

this is 100000 times more useful than attending lectures

@indian_street_view 5 жыл бұрын

You made this so simple, even non mathematical background students can understand this. You have no idea how your videos helping me in my career. I can't thank you enough for this

@quelesvalgareata1838 2 жыл бұрын

@statisticsfun 11 жыл бұрын

Great question! It is "degrees of freedom" or df. The reason we use 2 is because we have 2 variables (x and y) in this case. If we had more than 2 variables like x, y, and z the df would be n-3. In an earlier video I show how the regression line is forced through the point where the mean of x and y intersect. These "2" points are not included in the "average of the errors" because the error at these 2 points is 0. I need to create a video on d.f. for sure.

@prathameshpradipdatar2003 3 жыл бұрын

Awesome!

@DL-rw1fw 3 жыл бұрын

Thank you for this awesome video! I feel we should divide R2 by (n-1) and divide the standard-error-of-the-estimate by n. R2 uses an average y value from the sample. However, this average y value in the sample might not be the same as the average y value in the whole dataset. Thus, we have to divide R2 by (n-1). Here is the detailed explanation: stats.stackexchange.com/a/87422/318006 For the standard-error-of-the-estimate, since we do not use the average value from the sample, it might not be necessary to divide it by (n-1) or (n-2)

@modemnaveen6240 Жыл бұрын

@statisticsfun Can you please explain what's the difference between RMSE and Residual standard error (RSE) ?? We are diving by N for RMSE which gives baised estimate of deviation due to which we are dividing by degrees of freedom . Is that correct ? If yes , Is it better to use RSE in all cases instead of RMSE ?

@Coreyrob26 9 жыл бұрын

Every stat student should have to watch something like this so they can understand why they shouldn't be intimidated learning this stuff. You did an excellent job with this series of videos, thank you so much.

@statisticsfun 11 жыл бұрын

Thank you for the feedback, much appreciated. Make sure you like MyBookSucks on FaceBook (see link in video description). This will help other students find the educational videos and help them "see" too :).

@thehokipoki 10 жыл бұрын

After watching your videos I'm finally learning how to do this and pass my class. Thanks so much!

@daxdasche6112 4 жыл бұрын

May I just say sir that you are marvellous at this. Your explanation style, calm voice, uncluttered wording, steady pace to let it sink in, all works so well for me, and it seems from below, others too. Well done.

@statisticsfun 11 жыл бұрын

Aren't you sweet! Make sure you give me some love on FaceBook and Like MyBookSucks (see link in video description). This will help others find the educational videos and fall in love with me too.

@statisticsfun 11 жыл бұрын

Thank you and I appreciate the feedback. Make sure you like MyBookSucks on Facebook (see link in video description). This will help others find the educational videos.

@statisticsfun 11 жыл бұрын

The link to the playlist on regression is in the video description (of this video). KZfaq does not allow me to add links in comments.

@ALV57 7 жыл бұрын

Awesome explanation. My instructor was impossible to follow but you made this very clear and showed how simple it really is. I learned more in the first 3 minutes of this video than I did in the whole hour of my class.

@statisticsfun 11 жыл бұрын

Bridgette, yes I do. This video is part of a larger playlist. If will see a link to the entire playlist in the video description. In the second video I discuss how to calculate all the coefficients.

@hendrikl2906 3 жыл бұрын

this guy explains in 3 minutes what a teacher can't in 1.5 hours. Thank you!

@statisticsfun 10 жыл бұрын

You are very welcome (remember this channel is call Statisticsfun). Make sure you like MyBookSucks on Facebook (see video description for link). This will help others find the educational videos.

@joeschmoe1072 5 жыл бұрын

Of about four videos I tried to watch on this subject yours was by far the most well done and easy to understand - thank you!

@statisticsfun 11 жыл бұрын

I would appreciate you sharing these with your friends and colleagues. This helps me get the word out about the educational videos. If you have not done so, make sure you like MyBookSucks on FaceBook (see link in video description). This will help me spread the word about the free videos.

@alghamdiosamah9872 8 жыл бұрын

Thank my professor Dr. David, you make the statistic more fun for me. I never forget your amazing teaching at Avila University

@saad4q 6 жыл бұрын

Wow, the simplest and most straightforward way to explain Regression. This is better than everything I've read and seen.

@statisticsfun 11 жыл бұрын

Thanks for pointing that out. I added a link in the video description to the playlist. Hopefully the playlist can give you more insight into the nature of the formula's especially the first video. I appreciate your feedback too because the pace and detail of the videos is always a struggle for me. Good luck on your classes too.

@sadafmustafa7941 3 жыл бұрын

I usually don't make comments on any videos but I must say you are an amazing teacher, Stats never made sense to me and you have done an exceptional job!

@robbiedeegan3121 3 жыл бұрын

Thank you for making this. 8+ years later and still helping others (like myself) understand stats

@raevim7586 3 жыл бұрын

yes!! esp now that we have ol class

@ronniegirl69 8 жыл бұрын

Thank You so much, I've been struggling with this chapter, and getting behind in class, because, I couldn't move one until I figured this out. With your awesome video, I got it!!!!!! Excellent Teacher!!!!

@faadi4536 2 жыл бұрын

Such an amazing Simplification..I am learning machine learning and I have to start building machine models but I didn't how regression line was being calculated. You made it so clear for me. Kudos to you brother.

@statisticsfun 11 жыл бұрын

Thank you and is always good to hear the videos are helpful and informative.

@statisticsfun 12 жыл бұрын

@Norfeldt That is good information for me to know, btw, what country do you live in?

@statisticsfun 11 жыл бұрын

Very good to hear. Make sure you like MyBookSucks on FaceBook (see link in video description). This will help me spread the word about the videos.

@m.d.332 8 жыл бұрын

these tutorials make my day.It helps me understand statistics in a easy way.thanks a lot

@DeboleenaDutta29 9 жыл бұрын

BEST! I cannot thank you enough. I'll be studying in the next semester but for research paper, I needed to understand it well, and you take all the credits :D

@statisticsfun 12 жыл бұрын

@Norfeldt Very good question. The reason is we are estimating two variables b1 and b0. The larger the sample size the less impact this subtracting two will have.

@danil.torresashbridge1119 11 жыл бұрын

great video, I'm been searching all over trying to figure out all plots on a straight line and it's standard error of estimate. You didn't even tell us and I figured it out :) Thanks so much.

@alexvech 9 жыл бұрын

short, clear and straightforward ! keep going mate !

@yanavanina9754 3 жыл бұрын

*Only 18* 👇👇👇 413854.loveisreal.ru

@statisticsfun 11 жыл бұрын

Wonderful that you are catching on to statistics.

@statisticsfun 10 жыл бұрын

That is what I am talking about! "Party More Study Less!!!!"

@priyandumbajpayee4398 3 жыл бұрын

Why -2 in denominator i.e. n-2, why not some else number

@TricksticKx 2 жыл бұрын

@@priyandumbajpayee4398 "Great question! It is "degrees of freedom" or df. The reason we use 2 is because we have 2 variables (x and y) in this case. If we had more than 2 variables like x, y, and z the df would be n-3."

@statisticsfun 11 жыл бұрын

Great to hear and thanks for the video back. I have thought for sometime now that animation is the way to teach.

@faridhuseynov9185 9 жыл бұрын

Excellent tutorials. Thank you for clear explanations !

@mitchellmeyer4177 4 жыл бұрын

Im at working trying to dig this stuff out of my brain from my old statistics class no one has been able to help. 1:30 into this video and I got it down. Thank you

@emanuel5109 4 жыл бұрын

Thanks for clarifying the difference between R squared and Mean Squared Error. Great video!

@lidconsultation 7 жыл бұрын

All you’re your videos are very helpful. I can grade these as excellent.

@skibumanne 12 жыл бұрын

wow, thanks so much for your quick and understandable response! It's been my goal for years to learn this and understanding it is so very rewarding.

@statisticsfun 12 жыл бұрын

@skibumanne Typically both the standard error of the estimate and R^2 are used. Of course if R^2 = 1, standard error of the estimate (SE) would be 0. They both tell us how good of fit, but R^2 tells us a bit more. For example an R^2 of .45 means the regression explains about 45% can be explained by the linear relationship. You would use the SE if you were going to show the upper and lower bounds (or interval of the regression line). Good to know about the m and b too -- thanks.

@avrrao1940 6 жыл бұрын

Very good presentation - clear and simplified. Thank you.

@TheKaushik1983 6 жыл бұрын

Precise, to-the-point ! Loved it..

@CPZarolawala 9 жыл бұрын

I am really very thankful to you for such a very good explanation. I would recommend these lectures to others to clear their basics. Now I am going to see all videos with the relevant topics on youtube. Please let me know if you have more and other topics on logistics regression and other regression models used in financial and statistical modeling. Thanks and Regards - Chirag Patel

@harunsuaidi7349 2 жыл бұрын

The color coding and animations are really helpful!

@statisticsfun 11 жыл бұрын

Thanks for pointing that out. I had a typo in the link that I have corrected now.

@statisticsfun 10 жыл бұрын

You will see R2 (r squared) most of the time and in fact there is a strong relationship between R2 (r squared) and standard error of the estimate.

@sichonechanda9412 8 жыл бұрын

Thanks Sir, you the best. Youve really helped me out. God bless

@MAbdullah47 10 жыл бұрын

Thank you very much your tutorial is very useful and things become much easier when I watched your video series.

@statisticsfun 11 жыл бұрын

The short answer is this is degrees of freedom, the reason 2 is used is because there are two variables estimated. The y intercept and the coefficient of the independent variable or slope of line. As the number of observations increase this n-2 adjustment becomes less and less important. Make sure you like MyBookSucks on FaceBook (see link in video description). This will help others find the educational videos.

@nagendrahunsur5552 7 жыл бұрын

thank you for your efforts to make it so easy to understand, u r the best

@statisticsfun 11 жыл бұрын

Yes I believe the MMSE (minimum mean square estimate) is the same thing as least squares used in linear regression.

@armansh7978 4 жыл бұрын

I really really appreciate your effort to make such a so useful and brilliant video like this, also other your videos. thank you so much, indeed.

@somu9083 4 жыл бұрын

best video for understanding, before this I could not understand for one semester now it is clear in 10 minutes

@vmehighlow4481 8 жыл бұрын

Thanks for the clear explanation, Helped me a lot!

@elizabethhankammer5698 9 жыл бұрын

These tutorials make statistics easier to handle, thanks very much for the time to share your knowledge and skills. :)

@statisticsfun 9 жыл бұрын

***** You are very welcome. Good luck in your studies too.

@vsadha5241 Жыл бұрын

@@statisticsfun negative values how to avoid sir in linear regression

@Challenze 3 жыл бұрын

Thank you! Simple and easy to understand example.

@rajvattakunnel2022 3 жыл бұрын

Very good video; easy to understand and takes step by step / slow

@NareshKumar-ld1sk 11 жыл бұрын

all the vedio series are excellent and helpful. i will share with my friends and colleauges

@deliadykes6892 6 ай бұрын

wonderful! Happy Holidays!

@dimitrismavridis2179 10 жыл бұрын

Indeed, your explanation is great!

@faerafaaaw 11 жыл бұрын

This is how people will make this. Extremly instrucitve and good. My friends will know about this vids. Thanks man.

@1ragavan 5 жыл бұрын

Your videos are really awesome and superb animation will explain deep-rooted concepts in just plain terms is an art Thanks for your effort to make the animation part to easily understandable. Goodos to you

@BonMosh 4 жыл бұрын

you are genius man. you saved my life with this vedio

@MoistSodaCan 11 жыл бұрын

I would like to thank you for posting this video now i have a more clear view of what i have been doing

@emilyedwards4841 5 жыл бұрын

Thank you for this video! It was clear and easy to comprehend. Can you explain how the standard error of the estimate has a direct relationship with the SD of the criterion and an indirect relationship with validity?

@statisticsfun 11 жыл бұрын

The Standard Error of the Slope is what you are trying to find. You take the standard error of the estimate divided by sum of the differences of the x values squared. Sb1=Syx/Square Root(SSX)

@lawrence2467 4 жыл бұрын

Thanks a lot for this straightforward tutorial video!

@kailene5430 5 жыл бұрын

Thank you excellent job of explaining. Broke it down so it was easily understandable.

@bluemesa5341 7 жыл бұрын

+statisticsfun Could you please explain why we have to subtract 2 from number of observations 2:45. I know it's based on a derivation, but there should be reason behind it. Appreciate your help. Thank you!

@amithvalentine1479 3 жыл бұрын

Thank you for the videos, these are great!

@AshiPongener 10 жыл бұрын

Party more study less is what 'm doing because of your videos! Inspiring!!! :) Ty

@dorjiwangchuk3632 8 жыл бұрын

Very convincing...wish to see such teachers

@majnejati 2 жыл бұрын

Thanks for the detailed explanation. May I ask why the degree of freedom for this is -2 ? like instead of -1 ?

@zeeshanqasim8925 4 жыл бұрын

Thank you, sir, for your gorgeous services. I will appreciate if you please make a video of the drawing and understanding the box plots that are ubiquitous in research articles.

@bazas450 5 жыл бұрын

Honestly, you teach better than most lecturers. You should have more subscribers 👍. Just one question, in what situation would you use the regression line?

@nimfadagunton5616 6 ай бұрын

Very well explained, thanks so much.

@meganmagnuson1930 9 жыл бұрын

Thank you for the tutorials. My text book truly does suck and your tutorials are saving me in my online course. Very clear, concise and simple. This non-math minded person greatly appreciates them.

@statisticsfun 9 жыл бұрын

Megan Magnuson Megan, thank you so much for taking the time to write me -- it is much appreciated. If you get a chance like, share the videos. It helps get the word out. Liking our FB page helps too. www.FaceBook.Com/PartyMoreStudyLess

@statisticsfun 11 жыл бұрын

The standard error of estimate is very similar to the standard deviation. So comparing standard error the estimate is similar to comparing the standard deviation and the mean. In the case of a regression you have a lot of means (or actual values). You would want to compare 14.220 to the actual predicated value at that point as well. Keep in mind the standard error of the estimate is the "average error" not the specific error rate. Hope that helps.

@statisticsfun 11 жыл бұрын

I know! I was just joking around as well. I do appreciate the comment and I understood it perfectly.

@WorldThinker09 10 жыл бұрын

Thank you very much, it is good explanation to understand the regression analysis to apply for error estimation.

@chengzhang265 8 жыл бұрын

Hi, thanks so much for this easy understandable video. I have a question here. Do you know if the standad deviation of the Standard error of estimate will be an interesting parameter? What about if I compare between the STD of the actual value and the STD of the SEE? Can lower STD of SEE shows that the predicted errors vary less than the actual data, then conclude that the linear regression have acceptable prediction errors? Thx so much!

@statisticsfun 8 жыл бұрын

+Cheng Zhang I think that sounds like an interesting approach and could work.

@darkeoinment477 7 жыл бұрын

Thank you Mr. Fun, you are a great teacher. God bless. Please make more videos and party more.

@Sunshine-zi7oy 4 жыл бұрын

you are such a wonderful teacher.. thank you so very much🌷🌷

@2011jiqbal 9 жыл бұрын

wow.. you are an amazing teacher. God bless

@osamamelhem 7 жыл бұрын

Thanks so much for the clear video. What is the equation of the standard error of the mean? Thanks in advance.

@ranyael-shirbini8600 10 жыл бұрын

Hi, thanks for these videos they are so easy to follow! Just wanted to ask if its the estimated value-actual value or actual value-estimated value. In my text book its actual value -estimated value, or they show it as Square root of SSE/n-2. Thanks again!

@yourmusicdoctor62 Жыл бұрын

you just saved my semester. Its like you just took the burden away

@SigmaMotivatlon 2 жыл бұрын

You helped me explain standard error in my report for university thanks

@sharayu8876 3 жыл бұрын

Thank you for video! It was very helpful but can you please also share link/playlist to Regression analysis from first using the least square method? Also what’s is scatter plot in regression??

@azamatkarimov693 Жыл бұрын

Thanks Allah you were sent to help us . Thank you very much it is much easier with you . never stop making outstanding videos and we will never stop liking it

@lonelyjokers4 7 жыл бұрын

learned way more watching your playlist than in have in actual class

@statisticsfun 12 жыл бұрын

@Norfeldt The b0 is the y intercept and b1 is the slope of the line. If you had three variables (x, y, and z), then you would have n-3. And Yes, it does have to do with the degrees of freedom. Degrees of freedom are the number of variables that are "free to vary." As samples sizes get large there is less of an impact of this goofy denominator.

@Ghosty_panda 6 жыл бұрын

thank you it was simple and saved alot of time

@kingelias7038 6 жыл бұрын

Better than 95% of my lectures in uni !!!!

@ehsanzaferasa 10 жыл бұрын

MashAllah, your presentation in the form of a video is great and the manner of explanation is very explicit and crystal clear. Would request to have access to more these educational videos through links in response to this comment. I'm preparing for the CMA course and this video was just awesome!

@Norfeldt 12 жыл бұрын

@statisticsfun Thank you once again for the reply. In my country we normally use "a" as the slope and "b" as the interception which is why i didn't recognized it. I'm all set with your answer and looking forward to your next video :-)

@skibumanne 12 жыл бұрын

Any chance you have an example of when we'd be interested in the standard error of the estimate as opposed to R2? I'm trying to imagine what each value means in terms of answering a research question. To add to the country differences, in Canada we use "m" as slope and "b" as incercept. (y=mx+b)