I am using example from here: https://thinkingneuron.com/data-science-interview-questions-for-it-industry/#What-is-RMSE
Root Mean Squared Error:
- Find out the difference between original and predicted values for each row.
- Square the differences
- Sum all squared differences
- Take the average of the above sum
- Take the square root of above average
We see from table that RMSE = 14.2.
Here is what and how I calculated from data presented in table and method described above table:
$(25-20)^{2} + (30-31)^{2} + (29-33)^{2} + (40-38)^{2} = 46$
$\frac{46}{4} = 11.5$
$\sqrt{11.5} = 3.39116$
So in table we have RMSE = 14.2 and from my calculation RMSE = 3.39116. Is there mistake in table or in my calculations?

Good day,
You sure it is RMSE (Root Mean Square Error)?
And not MAPE (Mean Absolute pErcentage Error?)
The page seems to be wrong, or your screenshot?
Actually someone was also confused by this.
https://thinkingneuron.com/data-science-interview-questions-for-it-industry/#What-is-RMSE
From the website at
On the webpage It's 5 columns. In your screenshot It's only 4 columns.
Your screenshot:
on the webpage it looks slightly different, and is instead:
(12-10)²+(14-13)²+(18-15)²+(20-23)²+(11-15)² = 39
39
as in the webpage screenshot@ SUM: 39
Mean(SUM): 7.8 39/5 = 7.8
RMSE: 2.79 $\sqrt 7,8$ = 2.7928
webpage screenshot: https://thinkingneuron.com/wp-content/uploads/2020/06/How-to-calculate-RMSE.jpg
This was a interesting question, I'll follow this.
Hope it solves itself.
Regards Will