Hi, thank you for your video, it was very informative and useful. I have a problem that I am trying to resolve... Maybe you can help me. I have historical data of balances on my accounting books. I am trying to figure out what the "normal balance range" should be for each account, for example the account should have a balance between -100,000 and 200,000, this way I will have an interval that will trigger further investigation of the balance in case it is ever outside this range. The first thing I did was standardize the data, but now I need to return to the original values to construct the "normal range", how can you do this?
Hello sir, I'm confused about the norm.dist and standardize functions, as far as I know the norm.dist function is also to find zscore, but doesn't standardization also use the same formula to find zscore? Then why are the results different? CMIIW
thank you for real. i wonder if there are some zero price data or some messing price data, must we delete these days or make them somehow? i hear there is a approach and we can make five days data by running a geometric codes in mathlab but i don't know how...? i wonder if you know more details about what i'm talking about...
hy if i have a likert scale questionaire response like high moderate low and no how can i normalized in values to calculate minimum and maximum plz reply
I think the above comment is asking how to change the representation of a negative number from the minus symbol preceding the number to the brackets, which is how you have it. OP, right click on a cell(s) you’d like to change and click on the format cells option in the drop down. From there, go to the number category and there will be a list of how you would like negative numbers represented. Hope that helps :D
So, how do they "normalize" data (ie. closing price) to map to a range, ie: oscillators where prices may be "normalized" between -100 and 100 (overbought and oversold)?
Once they convert the set of numbers to values between 0 and 1, just multiply each number by 200 then subtract 100. .25 becomes -50, .75 becomes 50, 0 becomes -100...and so on.
Excellent explanation! Clear & concise! - Thankyou from Oz!
best video on data normalization, to the point
Awesome! Very useful, finally understood the concepts
Excellent video & fantastic explanation!!! Thank you very much!!!
Learnt a lot through this video...thanks so much...God bless you.
Thank you!
Use F4 key to select "Absolute Cell Reference" :)
Thank you!!!!! Great video!!!!!
Absolutely Mesmerizing, Thanks a lot for such an amazing description
Q: why did you normalise & standardise with the % change and not actual (closing) data? Is there a reason to chose one over the other?
@Keshav Agrahari hi Kesh
Legit question. Would like to know as well.
excellent Really!!
Thanks a lot sir. Beyond doubt learnt a lot.
Very helpful! thanks a lot!
Your video is great. Thank you :)
Hi, thank you for your video, it was very informative and useful. I have a problem that I am trying to resolve... Maybe you can help me. I have historical data of balances on my accounting books. I am trying to figure out what the "normal balance range" should be for each account, for example the account should have a balance between -100,000 and 200,000, this way I will have an interval that will trigger further investigation of the balance in case it is ever outside this range. The first thing I did was standardize the data, but now I need to return to the original values to construct the "normal range", how can you do this?
Great analysis, I personally questioning return of BRK shares under performing compare to spy , he benefiting his fame ,
top lad nice one g
A big merci (:
the formula u showed for STANDARDIZE is the formula for z-score
Hello sir, I'm confused about the norm.dist and standardize functions, as far as I know the norm.dist function is also to find zscore, but doesn't standardization also use the same formula to find zscore? Then why are the results different? CMIIW
When you said "Lets go ahead and populate that down to the bottom..." what did you hit to make the numbers autofill down like that?
I double left mouse clicked on the "autofill handle"...that little green square at the lower right of the selected cell.
thank you for real. i wonder if there are some zero price data or some messing price data, must we delete these days or make them somehow? i hear there is a approach and we can make five days data by running a geometric codes in mathlab but i don't know how...? i wonder if you know more details about what i'm talking about...
How do you deal with negative numbers after calculating the percentage change? All your negative numbers are in brackets and represented as positive.
hy if i have a likert scale questionaire response like high moderate low and no how can i normalized in values to calculate minimum and maximum plz reply
Can you normalize promotion type that has qualitative info ?
Lucid explanation.
showed how to do these 2 operations... but didnt explain why/when you would use 1 over the other on your data
How did you get the max and min values
Use the Excel MIN and MAX functions which will give the min and max values in a range =MIN(A1:A100)
how did u get brackets instead of - symbol
I'm not sure what you're talking about. What is the time elapsed when you observe the brackets?
I think the above comment is asking how to change the representation of a negative number from the minus symbol preceding the number to the brackets, which is how you have it. OP, right click on a cell(s) you’d like to change and click on the format cells option in the drop down. From there, go to the number category and there will be a list of how you would like negative numbers represented. Hope that helps :D
So, how do they "normalize" data (ie. closing price) to map to a range, ie: oscillators where prices may be "normalized" between -100 and 100 (overbought and oversold)?
Once they convert the set of numbers to values between 0 and 1, just multiply each number by 200 then subtract 100.
.25 becomes -50, .75 becomes 50, 0 becomes -100...and so on.
@@spreadsheetgeek4070 Thank you so much.