sampling with replacement sentence in Hindi
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- Note that there are some duplicates since a bootstrap resample comes from sampling with replacement from the data.
- In statistics, "'bootstrapping "'is any test or metric that relies on random sampling with replacement.
- Since we are sampling with replacement, we are likely to get one element repeated, and thus every unique element be used for each resampling.
- From this perspective, the case labeled " Surjective " f " " is somewhat strange : Essentially, we keep sampling with replacement until we've chosen each item at least once.
- In the terminology below, the case of sampling with replacement is termed " Any " f " ", while the case of sampling without replacement is termed " Injective " f " ".
- This is vaguely comparable to the coupon collector's problem, where the process involves " collecting " ( by sampling with replacement ) a set of " X " coupons until each coupon has been seen at least once.
- In order to reason about the population, we need some sense of the sampling with replacement so, assuming N is sufficiently large, for all practical purposes there is virtually zero probability that it will be identical to the original " real " sample.
- Note however that you can never explicitly " determine " the number of different words in the bag by sampling with replacement, but you can " estimate " it with decent precision . talk ) 18 : 31, 1 August 2014 ( UTC)
- Because of the simple " sampling with replacement " scheme in this second case, the urn content is now " static ", but this greater simplicity is compensated for by the assumption that the urn content is now " unknown " to an observer.
- In both of these models, the act of measurement has an effect on the outcome of future measurements . ( For comparison, when sampling with replacement, observation of a particular value has no effect on how likely it is to observe that value again . ) Note also that in a P�lya urn model, successive acts of measurement over time have less and less effect on future measurements, whereas in sampling without replacement, the opposite is true : After a certain number of measurements of a particular value, that value will never be seen again.
- On the other hand, the row labeled " S " n " orders " means that ordering doesn't matter : Choice ( 4, 7 ) and ( 7, 4 ) are equivalent . ( Another way to think of this is to sort each choice by the item number, and throw out any duplicates that result . ) In terms of probability distributions, sampling with replacement where ordering matters is comparable to describing the joint distribution of " N " separate random variables, each with an " X "-fold categorical distribution.
- One of the reasons for interest in " this particular " rather elaborate urn model ( i . e . with duplication and then replacement of each ball drawn ) is that it provides an example in which the count ( initially " x " black and " y " white ) of balls in the urn is " not " concealed, which is able to approximate the correct updating of " subjective " probabilities appropriate to a " different " case in which the original urn content " is " concealed while ordinary sampling with replacement is conducted ( without the P�lya ball-duplication ).
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