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  2. Lambert W function - Wikipedia

    en.wikipedia.org/wiki/Lambert_W_function

    The product logarithm Lambert W function plotted in the complex plane from −2 − 2i to 2 + 2i The graph of y = W(x) for real x < 6 and y > −4.The upper branch (blue) with y ≥ −1 is the graph of the function W 0 (principal branch), the lower branch (magenta) with y ≤ −1 is the graph of the function W −1.

  3. Tukey's range test - Wikipedia

    en.wikipedia.org/wiki/Tukey's_range_test

    This q s test statistic can then be compared to a q value for the chosen significance level α from a table of the studentized range distribution. If the q s value is larger than the critical value q α obtained from the distribution, the two means are said to be significantly different at level α : 0 ≤ α ≤ 1 . {\displaystyle \ \alpha ...

  4. Beta distribution - Wikipedia

    en.wikipedia.org/wiki/Beta_distribution

    In probability theory and statistics, the beta distribution is a family of continuous probability distributions defined on the interval [0, 1] or (0, 1) in terms of two positive parameters, denoted by alpha (α) and beta (β), that appear as exponents of the variable and its complement to 1, respectively, and control the shape of the distribution.

  5. Bonferroni correction - Wikipedia

    en.wikipedia.org/wiki/Bonferroni_correction

    The Bonferroni correction can also be applied as a p-value adjustment: Using that approach, instead of adjusting the alpha level, each p-value is multiplied by the number of tests (with adjusted p-values that exceed 1 then being reduced to 1), and the alpha level is left unchanged.

  6. Generalized gamma distribution - Wikipedia

    en.wikipedia.org/wiki/Generalized_gamma_distribution

    The quantile function can be found by noting that (;,,) = ((/)) where is the cumulative distribution function of the gamma distribution with parameters = / and =. The quantile function is then given by inverting F {\displaystyle F} using known relations about inverse of composite functions , yielding:

  7. Alpha vs. beta in investing: What’s the difference? - AOL

    www.aol.com/finance/alpha-vs-beta-investing...

    How to calculate alpha. ... To figure the expected return for an investment’s level of risk, analysts use beta, which measures an asset’s volatility and can be used to gauge risk. If a stock ...

  8. Exponential smoothing - Wikipedia

    en.wikipedia.org/wiki/Exponential_smoothing

    Exponential smoothing or exponential moving average (EMA) is a rule of thumb technique for smoothing time series data using the exponential window function. Whereas in the simple moving average the past observations are weighted equally, exponential functions are used to assign exponentially decreasing weights over time. It is an easily learned ...

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