Interpreting Linear Regression Results
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- Опубликовано: 9 ноя 2020
- This video describes how to interpret the major results of a linear regression...
...so I just noticed that this video took off. Thank y'all. You are most kind. Yes, I made some mistakes. you are correct...the Y is the DEPENDENT variable and the X is the INDEPENDENT variable. When I recorded this, it was for my undergrad students and it was off the cuff. I appreciate that it has helped you get through your own stats class. This video is designed for an undergrad stats student that will probably not go on to do major research so, clearly, there are plenty of details and stats stuff that I didn't do.
The link to the data is: www.kaggle.com/shivachandel/k...
I love this dataset because I usually finish the lecture with a tableau demonstration and most everyone realizes why the prices of these homes are so high..... 
Хобби
I FINALLY UNDERSTOOD THIS REGRESSION TABLE, GOT A 100 ON MY STATS TEST BC OF U YOURE MY HEROOOOO THANK YOU VERY MUCH DR
I am humbled by your comments and encouraged by your success. Thank you and congratulations to you.
I read the reading material for school, but you explained it in a way that made much more sense. Thank you so much!
you really helped me as i was doing my final year research project,cant thank you enough
This is the best video on explaining significance. Learned so much from this!
Superb!! Dr. Garcia guides how to pick up the right data points from the noise and how the relevant data points support answering the problem statement, thank you !!
Excellent and straight to the point. THANK YOU!
Hi, I like the way you explain statistics. I really appreciate the colors you use; I can focus better with no need to stop the video for a long time. Clear voice and speed just perfect. I'm an education psychologist graduate student; thinking on going further, probably statistics. Thanks for sharing.
Your video is very clear and easily understand the linear regression results. Thanks !
Best video I've seen on this topic. Thanks!
Love how you broke it down in to answering the 4 core questions and how to answer them
I was so overwhelmed by the subject but you made it so easy to understand! Thanks Dr. Garcia~
Glad to hear it!
Amazing video. I can see the light at the end of the tunnel 😅 Clearly explained. Thank you so much!
Thank you Dr. Garcia, appreciate it.
Thank you sir! This is such a great explanation, I was working on a project at work and you helped me a great deal!
Wow this helped me so much with my data analytics major project. Thank!
Thanks Sergio, I studied this years ago during my Degree but it got rusty for not using it. Now with your tutorial I remember it even better than then and I think this is one of the most detailed tutorials here! Most of them don't talk about the Alfa coeficient or not going on depth like you did. Thanks again!
thanks for the comment. I appreciate it.
Excellent explanation. Thank you.
you taught in this Vedio more than I learned in my whole semester. Thank you very much for upload this Vedio
Hello Sergio, this is an excellent walk-through; thank you for presenting this, and thank you for your dataset reference. I appreciate your clarification on your presentation focusing on a "single independent variable linear regression."
Super Explanation... Amazing
Thank you so much! Great and concise explanation paired with easy-to-understand language!
Enjoyed that - great explanation!
Truly amazing video!
Thank Sergio for this detailed explanation for the linear regression, very useful when i need to explain the result!
good to hear. thank you
wonderful explanation, bravo
Excellent video!
thank you man for this fantastic explanation video was really helpful
So helpful, this video is so amazing
Such a perfect video ,thank you so much.
Wow!!! Loved it!! 👍🏻👍🏻👌
Thank you so much, really helpful video for my dissertation project I'm working on at the moment. Only 3 weeks left 😢but this will definitely get me through it!
Good Luck! It'll be over before you know it!
this was an amzing video saved a student today thankyou
Thanks, very clear explanation
Thank you very much for a wonderful explanation!
Glad it helped!
Thank you! Well Explained!
Fantastically explained ! Thank you very much for having taken your time to help us
Thank you. Good luck in your course.
I finally understand i have been struggling to understand this topic
This is supper explanation. Thank you very much, it enhances my class work and add me confidence.
Confidence is key!
Thank you soooooo much.This is a great explanation!!!!!
your happiness is my happiness.
You are amazing! Thank you.
Thank you so much for taking time to explain regression! This vid put my mind on rest! :-)
My joy. Thanks.
Dr. Garcia is a literal god at statistics
He dident interpret the coefficients.
JazaKAllah ❤️very helpful
It's a good video, it's ctrl+shift+down is a life savior
Thank you for helping us with your knowledge and experience
Very helpful!
Excellent! Thank you so much!
Glad you liked it!
thank u Dr. Sergio.
Thank you.
Thank you for the great video..can you explain the analysis of standard error?
Thankyou for sharing!
Thank you very much Sir
This is so good
Currently doing my dissertation & one of my analysis methods is using regression models.
Cannot express enough how helpful this video was! Thank you so much🥹
thank you and good luck.
Thanks prof
thank you!!
Thank you
thank you so much
The ultimate goal of running a regression is to be able to predict/estimate the dependent variable. Right? How would you predict if the intercept is negative when you know that neither dependent or independent variables can be negative? Can we force it to zero intercept? If so, how?
Thanks for the video
my joy.
thank you
Thank you so much! :)
Perfect.
thank you a lot I am 2 hour a way from my exam and I was winder when F-significance rejects the null hypotheses 🙏
Is it a problem if standard error is around 300 if yes what might be the reason for it? I have taken small sample, so do I need to improve the data?
came for the content, stayed for the *SSSSSSSSSSSSSSSSIP* at 6:54. nice video
my students make fun of my coffee drinking all the time. lol.
THAAAAAANK YOU..JUST ABOUT TO DO MY EXAMS
Sergio, thank you so much! This helped a lot as I am working with this now the first time in my bachelor thesis. I wonder were the alpha comes from? Did I miss anything? Thank you again :)
You get to decide the alpha. (When doing homework, the problem or your professor will decide the alpha.) In the real world, you get to pick. This is implicit in applications such as six-sigma quality stuff...think ISO9001...but in reality, and certainly in academia, we know and report the three big alphas..(0.10, 0.05, 0.01) all at the same time by using those astrixes (or whatever the plural for asterix is). We can tell by the result what the highest alpha is where the variable is still significant. ;)
great
Great video! 4:09 May I ask what drawing software are you using to annotate the Excel file? Thanks.
The new Excel allows for drawing right into the spreadsheet..the real trick is to get a screen that allows the use of a pen..like the Wacom tablets....
It was really helpful thank u so much
You bet. good luck.
Hi, thanks. I have a large dataset of 100,000+ points. How does this affect the linear regression analysis? I got a very large F, an extremely small p value, and a small R^2.
Hi, it is really very helpful, clearing many doubts in an easy way. the one thing which I would request you to help me understand is why you were referring P value as 0.0000, however it is 2.416 in the regression model. please help what is that I am missing here.
Thanks for the video! Can you please send the link to the dataset?
link is now included in the description! thanks.
i want to learn how you connected a pen to you computer. what pen do you use? This is amazing how it helps in explaining and understanding
I have a Wacom tablet, which comes with a pen, and a screen capture software tool. easy cheesy.
@Sergio Garcia, Phd: Thank you for the video, it was very helpful. I am currently writing my master thesis and I had cited this video, my supervisor asked me to cite the original literature instead of this video. Do you have any research paper of your own or a book where you have formulated these 5 questions that one should ask while interpreting the regression results? Thanks :)
I do not. Any undergraduate stats book will tell you the same, you just have to learn how to read it. Your stats prof knows this and wants you to use your expertise which also relies on the texts you have already been presented with. Use your stats book and go back and read it again. It’ll make more sense. I promise.
Which good stats book you recommend sir?
What Excel add-in are you using for the "Draw" panel in the worksheet?
It's the basic Draw function. The real trick to have a pen screen like Wacom.
this is the most motherf*uckin' superb lecture I've ever attended! Thanks for it!
p.s. just create a full udemy course related with econometrics or data analysis, u'll earn thousands of dollar from it for sure!
How cool is that?!
It's the COOLEST!!
Sir thank you for your clear demonstration just got a question, if I am right the video is doing a single-tail test, if I am doing a two-tail test is it the same way to accept or reject the H0 by comparing the p-value of the coefficient with the significance level(i.e. 5%)?
The Ftest by definition is a one tail test. You can't do a two tail test in a regression. Technically, it is the same process when testing the pvalue, but it is a different distribution.
@@sergiogarciaphd7142 Thank you for the reply sir but I still wonder why a two-tail test cannot be carried out in a regression and also what distribution are you referring to? I apologise if the question is unnecessary, but I would greatly appreciate it if I can hear further explanation from you.
Which pen do you use
Hii, I have done my data analysis and the p value for the model as a whole is not significant, but one of the independent variable is significant. Can I still report it's results ?
have u performed multiple linear/nonlinear regression
Great Explanation! I watched all your videos w.r.t univariate & multiple linear regression on the same dataset and I too tried doing this. It works fine but i have a question(This question is w.r.t your other video on multiple linear regression on the same dataset) - Why have you removed waterfront, view and grade columns from the dataset? I understand those columns might not be required for the regression analysis but if I keep those columns while doing multiple linear regression, it seems like these 3 columns also impact price a lot. P value is 0 for view and grade as well which is less than 0.05 & 0.01.
Could you please explain this? if we assume these columns dont impact price value then their P value should be greater that 0.1 right?
Looking forward for your response.. Thanks!
I don't remember the results you are referencing off the top of my head, but there is a certain art to selecting variables of interest and measuring the impact. This is not usually a discussion for undergraduate courses but the impact of additional variables is a discussion for MULTIPLE linear regressions. That's a whole other ball game. This video is about interpreting the results of a simple single independent variable linear regression.
Great video, I understand now. Only thing I don understand is the "alpha", where did that come from? The smaller value of alpha means more tighter requirement?
You get to pick the alpha. (Your professor/supervisor/client will do this in practical application.) but when you are the decision maker, you pick the alpha...consider manufacturing where we use the six sigma process for quality....the alpha is, for all practical purposes about 0.01....that becomes the industry standard and it is in essence picked for you....but you get to decide the alpha...and more to the point when you use the decimals in the way you see it in the video...you can easily test any alpha.
good day sir, I just wanted to ask if an independent variable is not significant or does not have an explanatory power to the model but when removing it lowers the adjusted r-square what does this imply? so far the reason that i know the reason is because the t-statistic is greater than one. With this information, what can we infer?
It implies exactly what you described in the question. This is a classic trade-off situation. You, as the researcher, need to decide what is important. This is only one of many issues where researchers can disagree on results given the same data and methodologies. Sorry dude. no easy answer here. This is a classic, "What do YOU think?" question.
Can we conduct logistic regression analysis using excel?
the intercept's p-value is more than 0.1 How to interpret this
X is independent and Y is dependent variable
yes....*embarrased*
Hi Sergio, I have a question that has always troubled me. If the regression is significant (fvalue
uh...that's interesting, but not exactly what significance means....when we talk about significance, we are discussing the probability that the relationship between the two variables can/will be replicable if we run the test again with another similar/random/representative sample...and therefore predictable moving into future and we can then make decisions. So we're really talking about the big picture relationship between the two variables. I suggest you look at the residuals (Expected Value minus Actual Value) to see differences between observations. This means that some observations will be closer to their expected value, but that does not mean that any one point is more/less significant than any other.
@@sergiogarcia9044 Thank you very much for your reply! Regression analysis is often used in agricultural studies to examine the influence of rate on an outcome, say wheat yield. So, if three fertilizer rates, low, medium, and high, and applied to plots of wheat and the regression analysis result is that there is a significant positive linear relationship between fertilizer rate and wheat yield, can I say that the low rate is statistically different than the medium or high rate without performing pairwise tests between the yields from each rate of fertilizer? Or, is regression only saying that the relationship is significant, so if fertilizer is increased, yield will increase within the range tested (no extrapolation)?
@@4mfenme not really. In that scenario, you have 3 data points which is woefully small for a regression. You may be better served doing a t-test for differences between two groups which would show if there is a difference between the two groups or an ANOVA, which could include more than two. That is a classic hypothesis test question and often used in stats Exams..probably more so for Ag specific majors, but the point is the same. You gotta make sure you are using the right tool for the right question.
@@sergiogarcia9044 Thank you, Sergio!
Can anyone help me explain these numbers? coefficient: .049652, _cons .5150066, t 6.12 t 68.62 p>t 0.00 0.00 number of obs 6.665 prob > F 0.0000, R-squared 0.0056, I am trying to find out whether socioeconomic status can influence whether students find it important to perform better than other students in tasks. I am really bad at understanding these numbers.
Hi, I have produce a regression table just like yours in the vid, but with a different data sets. May I know the reasons why my significance-F is zero?
The significance of this F is also zero. Excell simply used the (E-70) to detail the decimal numbers are so small they have 70 zeros in front of them. Your zero is probably the same....some super small number that the software shows zero when displaying a smaller (usually 3) decimal places.
hi sir, i really need your help.
what if i got 0.00000 significant F? is that a good or bad sign? i mean.. it's too good? is it even possible? thankyou!!
Hi , i have got one silly question . at 11:02 , you said 'what is the relationship btwn dep(x) and indep(y) variable ?' does it not the dependant variable is the Y and the independent variable is the x actually ? I'm confused . Thankyou for your time .
yes. this was my mistake in the video.... the Y should be DEPENDENT. It DEPENDS on what happens on the other side of the equation. The X stands alone. It is INDEPENDENT. If you think back to all your high school algebra, we most often put y on the left and did the heavy lifting on the right side of the equation......we've been setting you up for regressions since Freshmen year Algebra the whole time.
Yea. You are correct. It is my mistake.
If my f = 0.013. Does this mean It doesn’t have significance?
What if I have only 20 observation but my R-squared is 0.99367. Is it normal for a small data to get this R-squared?
so....it's nice to have more observations..but that Rsquare is really good....almost too good?
I thought the coefficient have to be between 1 and 0, my results are pretty similar to yours with high coefficients and I was confused?
There are other methodologies where that is true, like a logistic regression. You may also be confusing coefficients with traditional probabilities......(emoji with guy shrugging his shoulders here).
Doesn’t X is independent variable and Y is dependent variable?
yes..yes it does.....(#facepalm)
Yes
ruclips.net/video/PaYqpOc-YNI/видео.html
Nice video! Just a little heads up: x is not dependant
yes, I am aware of the error..thanks. I never intended for this video to explode, but I have decided to leave it up because it is helpful. I have placed comments under the video to address this issue...
If x variables are inputs, shouldn't those be independent variables? Since the output (y) depends on x variables?
yes. you are correct. That is my mistake and it keeps me humble as more and more people watch (and correct) the video.
@sergiogarciaphd7142 Thank you for confirming. Your videos helped me pass my finals. I didn't forget this one since I had to dig. Worth it.
Great videos!
13:07 you rejected null hypothesis but isnt the p-value (2.417) bigger than alpha 0.01? Where did you get 0.000? Im confused
The p-value is NOT 2.417. It is 2.417e-70. which is 0.0000000...70 zeros....0002417. It is super super small. Excel is giving you a result of precision that is unnecessary and alerting you to the actual value by using the 'e'. This is NOT euler's constant. This is saying X 10^-70
@@sergiogarciaphd7142 Thank you so much for the clarification! Have a great day!
my questi
on is how is x axis dependent variable usually its the independent one
Yes. This has been addressed in comments many times. It was my mistake and you correct. The Y is Dependent and the X is Independent.