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.
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?
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.
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!
Absolutely would be great if you add Part 2! Thanks a lot for your work 🙏
Great tutorial! I would love to see a part 2. Thank you!
Yes please make a part 2, and thank you very much for this video, it was very interesting to watch ❤
Thanks! Very good explanation! Looking forward for the next part!
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
Thanks Kenji, I would love a part 2!!!
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 :)
I am literally using regression analysis in my investment class in MBA program. Thank you!
Thanks for all your help Kenji! 💪
Amazing!! I just discovered data analysis in excel with your video. Thank you very much!!!
Great Video. Looking forward to Part 2
We'd really love to see the Part 2! Thanks Kenji
Very helpful tutorial!!! Thanks Kenji :))
Glad it was helpful!
can't wait for part 2
thank
You are great man. Really. Well explained. and I subscribed.
We will be glad to have all that in one video
I want to know more about it, like seasonality and outliers
I like that your explanation is engaging and to the point
BRAVO 👍👍
Great very simple representation and easy to follow.
Thank you
You are welcome!
Waiting for Part 2 Kenji!!
Awesome. Thanks.
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.
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?
Awesome But I am Still waiting for Python & I am very excited for it
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 my bro
THIs is good stuff. THX
good stuff!
finally thankyou
thanks for watching :)
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.
We want part 2 for sure
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.
Part 2 please.
Please do a part 2
Are you familiar with lean six sigma, DMAIC ? Can you please do video of Analyze phase using excel
Kenji please start a separate playlist of videos of data analysis with python on youtube
can I employ Regression Analysis (multiple regression) for sensitivity analysis?
Please add part 2
want to know more.
❤
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!