I have no idea how could explain several complicated concepts in 12 mins, I'm not sure if it's because how smart you are or how deeply you can understand the concepts. I have been studying this for a whole semester and can't remember/understand a thing. Looking forward to other advanced regression tutorial!
Hello Kenji, thanks. my suggestion is to use TREND, INTECEPT and SLOPE. Also use the table with slicers so you can slice and directly see the result. Also use the r squared in the graph. YOu can also use LINEST to generate the data for multiple regression. good luck with part II
Would love to get a part 2 with seasonality as you said and also to remove outliers. We are testing how to predict the flow of water in a water treatment plant, based on rainfall and combined with oudoors temp (it minus deg C then water is in ice/snow) and maybe to predict the flow when in spring, it melts. Would love an example of that or similar that can be applicable.
Hi Kenji, thank you so much for all the beneficial content. Definitely subscribed to the Python course. I have a question here-is there a way that can help me interpret the numbers that show in the table? Interpretation is the hardest part for me.
thanks for taking the time to explain =) Do you reckon we should do the excel course first before we do the python one? Is there a discount if we take both? How are the classes like ya? Are they in ther form of video tutorials for self-learning?
Can I implement this to generate a forecast based on time series? I saw the forecast video, but if I can implement this along with time series, the results could be way more accurate.
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Thanks a lot . You explain a bulk of concepts in just 12 minutes. I am waiting for the Part 2. Vote for Part 2.
Absolutely, we have enough fundamentals to understand the regression using excel. I recommend to upload part two and I can't wait it.
+1 We want to learn more about regression model. It would be great, you make a more deepen part of regression.
100% we need a part 2! Can't wait!
Yes please make a part 2, and thank you very much for this video, it was very interesting to watch ❤
Absolutely would be great if you add Part 2! Thanks a lot for your work 🙏
I have no idea how could explain several complicated concepts in 12 mins, I'm not sure if it's because how smart you are or how deeply you can understand the concepts. I have been studying this for a whole semester and can't remember/understand a thing. Looking forward to other advanced regression tutorial!
Great tutorial! I would love to see a part 2. Thank you!
I am literally using regression analysis in my investment class in MBA program. Thank you!
Thanks! Very good explanation! Looking forward for the next part!
Thanks Kenji, I would love a part 2!!!
Thanks for all your help Kenji! 💪
Thank you very much for the helpful and clear explanation. Part 2 would be a great addition.
can't wait for part 2
thank
Very helpful tutorial!!! Thanks Kenji :))
Glad it was helpful!
We'd really love to see the Part 2! Thanks Kenji
We will be glad to have all that in one video
Great job of making this concept easy to understand! I'd like to see you do the Part II of this you mentioned as well. Thank Yo!!
Noted thank you :)
Amazing!! I just discovered data analysis in excel with your video. Thank you very much!!!
Thank you!🎉
Hello Kenji, thanks. my suggestion is to use TREND, INTECEPT and SLOPE. Also use the table with slicers so you can slice and directly see the result. Also use the r squared in the graph. YOu can also use LINEST to generate the data for multiple regression. good luck with part II
Great Video. Looking forward to Part 2
Great very simple representation and easy to follow.
Thank you
You are welcome!
You are great man. Really. Well explained. and I subscribed.
I want to know more about it, like seasonality and outliers
I like that your explanation is engaging and to the point
BRAVO 👍👍
Awesome. Thanks.
Waiting for Part 2 Kenji!!
finally thankyou
thanks for watching :)
THIs is good stuff. THX
Would love to get a part 2 with seasonality as you said and also to remove outliers. We are testing how to predict the flow of water in a water treatment plant, based on rainfall and combined with oudoors temp (it minus deg C then water is in ice/snow) and maybe to predict the flow when in spring, it melts. Would love an example of that or similar that can be applicable.
good stuff!
Thanks my bro
In just 12:33 minutes I now know and under simple and multiple regression analysis. I also vote for part 2, 3, 4, ......... n. 😁😁😁
Awesome But I am Still waiting for Python & I am very excited for it
Awesome.
Hi Kenji, thank you so much for all the beneficial content. Definitely subscribed to the Python course.
I have a question here-is there a way that can help me interpret the numbers that show in the table? Interpretation is the hardest part for me.
thanks for taking the time to explain =)
Do you reckon we should do the excel course first before we do the python one?
Is there a discount if we take both?
How are the classes like ya? Are they in ther form of video tutorials for self-learning?
We want part 2 for sure
Kenji please start a separate playlist of videos of data analysis with python on youtube
Please do a part 2
Part 2 please.
Please upload part 2 also
Please add part 2
Are you familiar with lean six sigma, DMAIC ? Can you please do video of Analyze phase using excel
Can I implement this to generate a forecast based on time series? I saw the forecast video, but if I can implement this along with time series, the results could be way more accurate.
can I employ Regression Analysis (multiple regression) for sensitivity analysis?
❤
Little bit lost on the p value how is that not great than 0.05
Same, it’s greater than 0.05
@@twothumbgaming8195 Because the decimal equivalent of that number (8.73335331340804E-08) is smaller than .05. It is equal to 0.00001%
I also got stuck here 5:39 , can someone please explain this? Thank you!
want to know more.