Sentence examples for bigger probability from inspiring English sources
It has a much bigger probability of success than putting $10,000 into a hot stock and waiting for it to double.
This happen because RL combination forwards first bundles with longer remaining TTL that have a bigger probability to reach the final destination, and drop first bundles with smaller remaining TTL.
This is happen because RL combination forwards first bundles with longer remaining TTL that have a bigger probability of reaching their final destination, and drops first bundles with smaller remaining TTL.
It is most robust in avoiding a reduced basis of poor orthogonality, with an almost zero probability of 0.001 to result in a minimum angle smaller than 45 o ; and (c) the problems themselves can have a bigger probability to have a minimum angle over [51.8 o, 67.9 o ], depending on which of LLL, DEEP, SLLL and PLLL is used to compare with PROB.
Typically, in a variation of the Allais experiment, subjects are asked to consider two different lotteries one with a big probability of winning a small prize and another with a smaller probability of winning a big one.
The results show the big probability of the absolute difference is within 0.1 when the snake robot is stationary.
By contrast, in the big-space approach, all the probabilities of a Bell-type model belong to one big probability space.
If the amplitude of coefficients in small scales is large, at a big probability, the amplitude of coefficients in corresponding big scales is large too.
Since a port may belong to different zones/roles with different probabilities, we define a port role as the MPCP zone it is most likely located (i.e., with the biggest probability distribution).
In the initial model, NO2 was strongly associated with APP, with more than five times as big probability for APP among those living in the quintiles with the highest NO2 levels compared to those with the least.
In particular, one can construct a big-probability space in which the conditional probabilities of outcomes, given a pair's state and apparatus settings, are equal to the corresponding unconditional probabilities in the many-spaces approaches: P xl & yr / λ & l & r) = Pλ l r xl & yr), P xl′ & yr / λ & l′ & r) = Pλ l′ r xl′ & yr), etc.
