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Multiple Regression | Coefficients - Interpretation, C.I, Hypothesis Testing
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- čas přidán 16. 08. 2024
- This is a short walkthrough of the coefficient portion of the multiple regression software output.
Part 1: F-test, R-square, Se: • Multiple Regression | ...
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00:00 Intro
00:21 Population and Sample Models
01:23 Constant or Intercept
01:47 Interpreting coefficients
02:47 Confidence Interval for Coefficient
03:52 Point prediction
04:32 t-tests
07:04 one-tailed test
Thanks for the clear and straight-to-the-point video. No lengthy intro and outro, but short with examples and visualizations. Great!
Thanks for the feedback, Cheeseopedia.
Glad you like it.
This is by far the best multi regression video I have seen
Wow, this video explained linear regression so clearly! I've been struggling to grasp this concept, but your explanation really made it click for me. Thank you so much, Joshua Emmanuel! Your dedication to educating young black people like me is inspiring. Please keep up the fantastic work - we need more educators like you empowering us to excel in these fields! 🙌💯
This was so helpful. It made my research into multi-factor models in finance much easier to understand. Thank you very much.
This was so clear! Everything makes sense now, thank you so much!
You're welcome, Tayana.
Thank you for these videos! They are very helpful!
outstanding explanation ! Thank you !
Prof Emmanuel to the rescue! I was trying to figure out what were these coefficient β that were pulled out of nowhere in my chapter about Design of Experiment
My pleasure. Thanks for dropping a note.
man this was great
more than what I expected it explained the whole thing together as a package
keep it on 🔥🔥🔥🔥🔥🔥
Thank you so much sir, but im unclear about 3:52, in the question it is stated as 10 years but while solving you used 96 months which was 8 years based on the conversion
You’re right. I changed the question to 96 months at 3:52 but forgot to go back and change it at the beginning (0:00). Thanks for pointing it out.
Amazing! that is exactly what I was looking for, thank you!
Thank you so much Emmanuel. This video is so explanatory.
This video is amazing, thank you!
This made so much sense. Thank you!!!!
for the t-tests, please explain why you use two-tailed test for the other variables and one-tailed test for the last variable.
7:03; if you’re testing whether the coefficient is positive or negative, then it is a one tailed test. If you’re simply testing for significance (without a specified direction), then it is a two-tailed.
@@joshemman thank you so much for the help and quick response
This Helped me a lot for my exam Tq so much 😊😊
thank you for your lecture
Thanks so much for this video
You're welcome.
Do you offer tutoring? You are a great teacher!
Hi,
I have a quick question. Why does it says “8-years” 4:13 when at the beginning 0:00 “c)…10-year-old”?
Thank you for the explanation, it is very clear and helpful!
I have a question what should I do if some of the parameters for example maintenance of the house depend on price,room numbers or region but not directly? is it correct to make this type of analysis with such parameters?
Very good ..m also a lecturer of statistics
Thanks for dropping a note. Much appreciated.
Thanks for the video!
I have a question.
When testing the significance of predictor variables, we used Beta not equal to 0 as Ha, but for Distance, we used Beta < 0.
Just like Distance, can we use Beta > 0 for the other independent variables?
If yes, can we also use Beta not equal to 0 for testing the significance of Distance?
Yes, you can use Beta not equal to 0 for testing the significance of Distance. I used Beta > 0 as an example of a right-tailed test.
@@joshemman Oh okay. Thank you for the quick reply!
Amazing
Hii, if i have a model that as a whole is not significant, but one of the independent variables is significant, can i still report the result just for that indeoendent variable?
Thank you for these videos
I have on question
how to a form product dd for the least period is given below period dd period 1,2,3,4,5,6,7,8,9 dd 44,52,50,54,55,55,60,56,62 develop a linear trend equation ,predict the dd value for the next period and find the regression equation solution
Use Excel or Google sheets:
X = 1,2,3,4,5,6,7,8,9
Y = 44,52,50,54,55,55,60,56,62
use
=SLOPE(Y, X)
=INTERCEPT(Y, X)
beautiful.
Don't understand y u use the student t test instead of the z test to construct the 95% confidence interval since the sample size was large thus greater than or equal to 30 and the standard error of population given
People use Z when sample is large just as an approximation since t-tables may not include large t values. Also note that the standard error is based on the sample, not population.
At 3.49, Actual value of Age coefficients is 1.35. At 95% confidence, Age values interval is between -3.8 to 6.6.
It means our regression coefficient from -3.8 to 6.6 is allowed or what?
You will say you are 95% confidence that the true Age coefficient lies between -3.8 and 6.6.
That is, with repeated sampling, you expect the true Age coefficient to be somewhere between those two values in 95% of the samples.
You can look up definition of confidence intervals to learn more.
How to estimate the ratio of MVP AND MFC
❤
Hi Prof Emmanuel. Please, I need ur email, I can't chat with you on LinkedIn either I quess I need to have a prenium account