Sentence examples for difficult probability from inspiring English sources

We give conditions for the strict monotonicity of ( D k k = 0 ∞ in some cases. The proof of limit assertion (5) uses a lemma (see Lemma 15 in [4]) with a rather difficult probability theoretical proof.

The reason for selecting this type of questionnaire for the participants of this study was that these types of questions were recommended, since according to McCafferty (1994), if the tasks are difficult, the probability of producing private speech will be higher.

Things are even more difficult when probabilities are subjective and individual beliefs may differ.

Not only that, they can do really quite difficult maths: statistics, probability, Bayesian theory... Gopnik has devised experiments showing that when it comes to designing and testing hypotheses, 18-month-old toddlers are better at it than adults.

This becomes more difficult when the probability distribution function of these random variables is assumed to be unknown.

It is difficult to obtain probability distribution functions (PDFs) that provide a complete representation of microstructural variability in three-dimensional polycrystalline materials using limited information since this inverse problem is highly ill-posed.

Findings that do not reach a level of statistical significance might still bear valuable information, but access to these findings is more difficult since the probability to find these published is lower (Franco et al. 2014).

However, the classification of the species is more difficult, increasing the probability of the existence of cryptic species among the known specimens [13], [14], and their detection purely by means of morphology appears unlikely.

For "difficult" items this probability would be lower than for "easy" items, relative to the individual person measure.

We show that the problem of finding high-multiplexing/high-coverage designs is subject to a computational phase transition, becoming dramatically more difficult when the probability that two primers are mutually compatible drops below a critical threshold.

We show that finding high-multiplexing/high-coverage designs is subject to a computational phase transition, becoming dramatically more difficult when the probability of primer pair interaction exceeds a critical threshold.