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are you sure you did this right? this looks funny to me. not trying to be mean but I think adding the percents is not the way to go? i think they are supposed to be combined by squaring them, adding them, and taking the square root,, i.e. root-sum-squaring, as uncertainties that are uncorrelated are developed to be combined as random variables like you'd add variances then take square root to get the final uncerrtainty. Like NIST Type A and B uncertainties and BIPM GUM?
I have past up from 9-12th grade from watching your math videos, and I've gotten complements from how much I have learned, and from how fast. thank you for what you do man, your making a real difference in the world!
Generally, the last significant digit indicates that you know that value within +/- half of itself (so, if you had a ruler with only inch markings, you could estimate something to within the nearest inch, because the best you could do is guess whether it was more or less than halfway to the next inch; if the ruler had 0.1 inch markings, you could easily determine how many tenths of an inch it had towards the next inch, but then you'd have to estimate whether it was more or less than halfway between two consecutive tenths of an inch). It seems unusual that you could have a value to 0.1 cm as the last significant digit, and not be estimating it +/- .05 cm. But, (using the examples from the end of the video, since the frame is paused on my screen) I suppose if your measuring system were actually at 1.2 cm intervals (0, 1.2, 2.4, 3.6), then you would have to report your measurement as one of those values +/- 0.6 cm. So, while somewhat unusual, one could report results to a significant digits place that is the same as the uncertainty measurement's place.
I don't really get the point of sigfigs when using these error intervals, other than brevity, but that's just rounding then, nothing to do with significance
Because the additional significant digits are essentially "false precision"; you can't get something more precise than the inputs you had to start with. So, after calculating the answer to however many digits, it has to be "trimmed back" to the amount of precision that you had available at the start.
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are you sure you did this right? this looks funny to me. not trying to be mean but I think adding the percents is not the way to go? i think they are supposed to be combined by squaring them, adding them, and taking the square root,, i.e. root-sum-squaring, as uncertainties that are uncorrelated are developed to be combined as random variables like you'd add variances then take square root to get the final uncerrtainty. Like NIST Type A and B uncertainties and BIPM GUM?
I have past up from 9-12th grade from watching your math videos, and I've gotten complements from how much I have learned, and from how fast. thank you for what you do man, your making a real difference in the world!
That plus minus sign haunts my dreams
Nah same
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Generally, the last significant digit indicates that you know that value within +/- half of itself (so, if you had a ruler with only inch markings, you could estimate something to within the nearest inch, because the best you could do is guess whether it was more or less than halfway to the next inch; if the ruler had 0.1 inch markings, you could easily determine how many tenths of an inch it had towards the next inch, but then you'd have to estimate whether it was more or less than halfway between two consecutive tenths of an inch).
It seems unusual that you could have a value to 0.1 cm as the last significant digit, and not be estimating it +/- .05 cm.
But, (using the examples from the end of the video, since the frame is paused on my screen) I suppose if your measuring system were actually at 1.2 cm intervals (0, 1.2, 2.4, 3.6), then you would have to report your measurement as one of those values +/- 0.6 cm. So, while somewhat unusual, one could report results to a significant digits place that is the same as the uncertainty measurement's place.
great explaination!! thank youu
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Thank you this helped me I was indeed struggling
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Wouldn't it be more accurate to add the errors in quadrature or am I mistaking that with propagation of errors?
.
Why was the 18 rounded to 20
Sig figs
8 is more than 5 that's why 1 is round of to 2 and 8 become 0
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thanks a lot for doing this video!!!
Shouldn't the centimeters be squared in the first example?
Thank you Ur the best❤
Very helpful. Thanks!
I don't really get the point of sigfigs when using these error intervals, other than brevity, but that's just rounding then, nothing to do with significance
what if you multiple AND divide in the same equation
Is it necessary to multiply with a hundred?
nah
I'm so going to pass my exams now 🥰
did u pass
Yes I did got a merit 😊
Why do you HAVE to round the results? Seems like you are deliberately decreasing precision.
Because the additional significant digits are essentially "false precision"; you can't get something more precise than the inputs you had to start with. So, after calculating the answer to however many digits, it has to be "trimmed back" to the amount of precision that you had available at the start.
How will you solve a whole number like 10 multiplied by an uncertainty of 30 plus or minus 2
just add the uncertainties. If your 10 is an absolute value with 0 uncertainty, you'll get 10*30 +_ 2, so 300 +_ 2
this doesn't really make sense especially when it's ignoring the propagation of uncertainties, am I missing something?
Thank you sir!
The division problem should be unitless
يعنى ايه uncertainty
Why not 19
Yes ,I also feel confused that but the crowd under comment say good😅😂😂😂
This is so wrong.. Where is the formula you are suppose to use? the e = square root of e1^2 + e2^2?
goat
Multiplying N cm x M cm should result in NxM cm2 (centimeter squared) not NxM cm !!!
💊
Addition of Percentage is Wrong 👎 !! Correct is 4.8440%
9:20, 1.8684*0.04864 is actually 0.090878976
Actually it's 4.0864% and not 4.864%
U forgot the 0 between 4 and 8
He got a pitching voice, this bores me