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  2. dc (computer program) - Wikipedia

    en.wikipedia.org/wiki/Dc_(computer_program)

    dc (desk calculator) is a cross-platform reverse-Polish calculator which supports arbitrary-precision arithmetic. [1] It was written by Lorinda Cherry and Robert Morris at Bell Labs. [2] It is one of the oldest Unix utilities, preceding even the invention of the C programming language. Like other utilities of that vintage, it has a powerful set ...

  3. Probability density function - Wikipedia

    en.wikipedia.org/wiki/Probability_density_function

    This probability is given by the integral of this variable's PDF over that range—that is, it is given by the area under the density function but above the horizontal axis and between the lowest and greatest values of the range. The probability density function is nonnegative everywhere, and the area under the entire curve is equal to 1.

  4. Digital comparator - Wikipedia

    en.wikipedia.org/wiki/Digital_comparator

    The binary variable (A=B) is 1 only if all pairs of digits of the two numbers are equal. Inequality In order to manually determine the greater of two binary numbers, we inspect the relative magnitudes of pairs of significant digits, starting from the most significant bit , gradually proceeding towards lower significant bits until an inequality ...

  5. Triangular distribution - Wikipedia

    en.wikipedia.org/wiki/Triangular_distribution

    This distribution for a = 0, b = 1 and c = 0.5—the mode (i.e., the peak) is exactly in the middle of the interval—corresponds to the distribution of the mean of two standard uniform variables, that is, the distribution of X = (X 1 + X 2) / 2, where X 1, X 2 are two independent random variables with standard uniform distribution in [0, 1]. [1]

  6. Cumulative distribution function - Wikipedia

    en.wikipedia.org/wiki/Cumulative_distribution...

    Cumulative distribution function for the exponential distribution Cumulative distribution function for the normal distribution. In probability theory and statistics, the cumulative distribution function (CDF) of a real-valued random variable, or just distribution function of , evaluated at , is the probability that will take a value less than or equal to .

  7. Joint entropy - Wikipedia

    en.wikipedia.org/wiki/Joint_entropy

    The joint entropy of a set of variables is less than or equal to the sum of the individual entropies of the variables in the set. This is an example of subadditivity . This inequality is an equality if and only if X {\displaystyle X} and Y {\displaystyle Y} are statistically independent .

  8. Skewness - Wikipedia

    en.wikipedia.org/wiki/Skewness

    In the older notion of nonparametric skew, defined as () /, where is the mean, is the median, and is the standard deviation, the skewness is defined in terms of this relationship: positive/right nonparametric skew means the mean is greater than (to the right of) the median, while negative/left nonparametric skew means the mean is less than (to ...

  9. Second partial derivative test - Wikipedia

    en.wikipedia.org/wiki/Second_partial_derivative_test

    Therefore, the second condition, that f xx be greater (or less) than zero, could equivalently be that f yy or tr(H) = f xx + f yy be greater (or less) than zero at that point. A condition implicit in the statement of the test is that if f x x = 0 {\displaystyle f_{xx}=0} or f y y = 0 {\displaystyle f_{yy}=0} , it must be the case that D ( a , b ...