Imagine that you did not account for the random uncertainty in your measurements
ID: 2076543 • Letter: I
Question
Imagine that you did not account for the random uncertainty in your measurements in the experiment you designed in part 1. Instead, you accounted for instrument uncertainty only. Would this have changed your judgement about the Bohr model? What have you learned about the importance of random uncertainty? (Please Help! Thanks!)
PS. Just let me know the importance of random uncertainty. And maybe how Bohr's model relies on uncertainty?
(Also, can u please answer these as well? Thanks! )
2) when the prediction and outcome of a testing experiment are not consistent, does this automatically mean the hypothesis you are testing should be rejected? explain.
3) when the prediction and outcome of a testing experiment are consistent, does this provemean the hypothesis you were testing? explain
Explanation / Answer
1. Importance of random uncertainty:- The errors or uncertainties which occurs irregularly and at random, in magnitude and directions are called random error. Such uncertainties occur by chance and arise due to slight variation in the attentiveness of the observer while taking the observations or because of slight variations in the experimental conditions. So it is impossible to get rid of random error, but science has a way to get around it. that take large number of observations and take there mean as the value of measured quantity. So it is always important to get rid of random uncertainties other wise our measurements will not be accurate. In case of Bohr's model each observation and calculations we does must be accurate so this experiment relies on random uncertainties.
2. It is not always true but this clearly means that we have to improve our measurement techniques and methods and all type of sources of errors must be taken into account. This is also possible that we do not have sufficient data and techniques to prove our hypothesis e.g Einstein's Theory of relativity is one of the famous example of such critical conditions. Also there are some hypothesis which cannot be proved directly.
As well if the predictions and outcomes are not consistent we have to modify our hypothesis but if after all modifications and experimentation results are not consistent the hypothesis may be rejected.
3. When the prediction and outcome of a testing experiment are consistent, this prove the hypothesis you were testing at this moment but the theory may get rejected in the future when we develop newer measurement techniques for example Rutherford atom model or Thomson's atom model