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[1] [2] A random sequence of events, symbols or steps often has no order and does not follow an intelligible pattern or combination. Individual random events are, by definition, unpredictable, but if there is a known probability distribution, the frequency of different outcomes over repeated events (or "trials") is predictable.
Gesell and his colleagues documented a set of behavioral norms that illustrate sequential & predictable patterns of growth and development. Gesell asserted that all children go through the same stages of development in the same sequence, although each child may move through these stages at their own rate [ 3 ] Gesell's Maturational Theory has ...
In psychology and cognitive neuroscience, pattern recognition is a cognitive process that matches information from a stimulus with information retrieved from memory. [1]Pattern recognition occurs when information from the environment is received and entered into short-term memory, causing automatic activation of a specific content of long-term memory.
The two may have common neurological bases, but no convincing scientific evidence supports this hypothesis. Brown (1973) conducted a study [1] on the acquisition of 14 grammatical morphemes by three English-speaking children and found that their developmental patterns were remarkably similar. This study is said to have initiated research in the ...
A numeric sequence is said to be statistically random when it contains no recognizable patterns or regularities; sequences such as the results of an ideal dice roll or the digits of π exhibit statistical randomness. [1] Statistical randomness does not necessarily imply "true" randomness, i.e., objective unpredictability.
After an event has occurred, people often believe that they could have predicted or perhaps even known with a high degree of certainty what the outcome of the event would be before it occurred. Hindsight bias may cause distortions of memories of what was known or believed before an event occurred and is a significant source of overconfidence in ...
Researchers in this study questioned whether domain generality of statistical learning in infancy would be seen using visual information. After first viewing images in statistically predictable patterns, infants were then exposed to the same familiar patterns in addition to novel sequences of the same identical stimulus components.
The inductive bias (also known as learning bias) of a learning algorithm is the set of assumptions that the learner uses to predict outputs of given inputs that it has not encountered. [1] Inductive bias is anything which makes the algorithm learn one pattern instead of another pattern (e.g., step-functions in decision trees instead of ...