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  2. List of logarithmic identities - Wikipedia

    en.wikipedia.org/wiki/List_of_logarithmic_identities

    Logarithms can be used to make calculations easier. For example, two numbers can be multiplied just by using a logarithm table and adding. These are often known as logarithmic properties, which are documented in the table below. [2]

  3. Natural logarithm - Wikipedia

    en.wikipedia.org/wiki/Natural_logarithm

    For example, ln 7.5 is 2.0149..., because e 2.0149... = 7.5. The natural logarithm of e itself, ln e, is 1, because e 1 = e, while the natural logarithm of 1 is 0, since e 0 = 1. The natural logarithm can be defined for any positive real number a as the area under the curve y = 1/x from 1 to a [4] (with the area being negative when 0 < a < 1 ...

  4. Logarithm - Wikipedia

    en.wikipedia.org/wiki/Logarithm

    In mathematics, the logarithm of a number is the exponent by which another fixed value, the base, must be raised to produce that number.For example, the logarithm of 1000 to base 10 is 3, because 1000 is 10 to the 3 rd power: 1000 = 10 3 = 10 × 10 × 10.

  5. Euler's formula - Wikipedia

    en.wikipedia.org/wiki/Euler's_formula

    In differential equations, the function e ix is often used to simplify solutions, even if the final answer is a real function involving sine and cosine. The reason for this is that the exponential function is the eigenfunction of the operation of differentiation .

  6. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    Thus, if the random variable X is log-normally distributed, then Y = ln(X) has a normal distribution. [2] [3] Equivalently, if Y has a normal distribution, then the exponential function of Y, X = exp(Y), has a log-normal distribution. A random variable which is log-normally distributed takes only positive real values.

  7. Log–log plot - Wikipedia

    en.wikipedia.org/wiki/Log–log_plot

    Setting = ⁡ and = ⁡, which corresponds to using a log–log graph, yields the equation = + where m = k is the slope of the line ( gradient ) and b = log a is the intercept on the (log y )-axis, meaning where log x = 0, so, reversing the logs, a is the y value corresponding to x = 1.