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  2. Power law of practice - Wikipedia

    en.wikipedia.org/wiki/Power_law_of_practice

    The power law of practice states that the logarithm of the reaction time for a particular task decreases linearly with the logarithm of the number of practice trials taken. It is an example of the learning curve effect on performance.

  3. Learning curve - Wikipedia

    en.wikipedia.org/wiki/Learning_curve

    A learning curve is a graphical representation of the relationship between how proficient people are at a task and the amount of experience they have. Proficiency (measured on the vertical axis) usually increases with increased experience (the horizontal axis), that is to say, the more someone, groups, companies or industries perform a task, the better their performance at the task.

  4. Hick's law - Wikipedia

    en.wikipedia.org/wiki/Hick's_law

    The logarithm expresses depth of "choice tree" hierarchy – log 2 indicates binary search was performed. Addition of 1 to n takes into account the "uncertainty about whether to respond or not, as well as about which response to make." [3] In the case of choices with unequal probabilities, the law can be generalized as:

  5. Log–log plot - Wikipedia

    en.wikipedia.org/wiki/Loglog_plot

    A loglog plot of y = x (blue), y = x 2 (green), and y = x 3 (red). Note the logarithmic scale markings on each of the axes, and that the log x and log y axes (where the logarithms are 0) are where x and y themselves are 1. Comparison of linear, concave, and convex functions when plotted using a linear scale (left) or a log scale (right).

  6. Forgetting curve - Wikipedia

    en.wikipedia.org/wiki/Forgetting_curve

    Some learning consultants claim reviewing material in the first 24 hours after learning information is the optimum time to actively recall the content and reset the forgetting curve. [8] Evidence suggests waiting 10–20% of the time towards when the information will be needed is the optimum time for a single review.

  7. Weber–Fechner law - Wikipedia

    en.wikipedia.org/wiki/Weber–Fechner_law

    At daylight levels, the curves are approximately straight with slope 1, i.e. log = log +., implying = / is constant. At the very darkest background levels ( B {\displaystyle B} ≲ 10 − 5 cd m −2 , approximately 25 mag arcsec −2 ) [ 24 ] the curves are flat - this is where the only visual perception is the observer's own neural noise ...

  8. Experience curve effects - Wikipedia

    en.wikipedia.org/wiki/Experience_curve_effects

    An example of experience curve effects: Swanson's law states that solar module prices have dropped about 20% for each doubling of installed capacity. [1] [2]In industry, models of the learning or experience curve effect express the relationship between experience producing a good and the efficiency of that production, specifically, efficiency gains that follow investment in the effort.

  9. Logistic function - Wikipedia

    en.wikipedia.org/wiki/Logistic_function

    The standard logistic function is the logistic function with parameters =, =, =, which yields = + = + = / / + /.In practice, due to the nature of the exponential function, it is often sufficient to compute the standard logistic function for over a small range of real numbers, such as a range contained in [−6, +6], as it quickly converges very close to its saturation values of 0 and 1.