### Representation

Posted:

**Thu Oct 18, 2018 7:59 pm**What does the numerical value given by the uncertainty principle actually mean?

Created by Dr. Laurence Lavelle

https://lavelle.chem.ucla.edu/forum/

https://lavelle.chem.ucla.edu/forum/viewtopic.php?f=19&t=34180

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Posted: **Thu Oct 18, 2018 7:59 pm**

What does the numerical value given by the uncertainty principle actually mean?

Posted: **Thu Oct 18, 2018 8:04 pm**

It gives a range of possible values that the velocity could take on. So, for example, if you have an initial velocity of 5m/s, and you calculated the change in velocity to be +/-2, the final velocity could be between 3 and 7m/s. It can sort of be compared to the margin of error, if that makes sense.

Posted: **Thu Oct 18, 2018 8:07 pm**

The uncertainty principle has two complementary variables for which there is a limit to the precision with which we can measure either. Essentially, there's the uncertainty in momentum and the uncertainty in position of a particle. These variables represent the precision to which either the momentum or position can be measured. The more precision you know one variable (corresponds with a lower value), the less precision you know the other variable (corresponds with a higher value).

Posted: **Sun Oct 21, 2018 4:33 pm**

Can you explain how the uncertainty principle is applied to real life situations? In a session today, we did an example that asked for the minimum indeterminacy of a bowling ball's position and if you coulf blame Heisenberg's Uncertainty Principle when you miss the pins and I don't really see how it connects.

Posted: **Sun Oct 21, 2018 11:49 pm**

The uncertainty principle has two complementary variables for which there is a limit to the precision with which we can measure either. Essentially, there's the uncertainty in momentum and the uncertainty in position of a particle. These variables represent the precision to which either the momentum or position can be measured. The more precision you know one variable (corresponds with a lower value), the less precision you know the other variable (corresponds with a higher value).