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2. Work sampling - Wikipedia

   en.wikipedia.org/wiki/Work_sampling

   Work sampling is the statistical technique used for determining the proportion of time spent by workers in various defined categories of activity (e.g. setting up a machine, assembling two parts, idle…etc.). [1] It is as important as all other statistical techniques because it permits quick analysis, recognition, and enhancement of job ...

3. Logarithm - Wikipedia

   en.wikipedia.org/wiki/Logarithm

   In mathematics, the logarithm is the inverse function to exponentiation. That means that the logarithm of a number x to the base b is the exponent to which b must be raised to produce x. For example, since 1000 = 103, the logarithm base of 1000 is 3, or log10 (1000) = 3.

4. Log-normal distribution - Wikipedia

   en.wikipedia.org/wiki/Log-normal_distribution

   Log-normal distribution. In probability theory, a log-normal (or lognormal) distribution is a continuous probability distribution of a random variable whose logarithm is normally distributed. Thus, if the random variable X is log-normally distributed, then Y = ln (X) has a normal distribution.

5. Logistic regression - Wikipedia

   en.wikipedia.org/wiki/Logistic_regression

   An explanation of logistic regression can begin with an explanation of the standard logistic function. The logistic function is a sigmoid function, which takes any real input , and outputs a value between zero and one. [2] For the logit, this is interpreted as taking input log-odds and having output probability.

6. Delta method - Wikipedia

   en.wikipedia.org/wiki/Delta_method

   Delta method. In statistics, the delta method is a method of deriving the asymptotic distribution of a random variable. It is applicable when the random variable being considered can be defined as a differentiable function of a random variable which is asymptotically Gaussian .

7. Anderson–Darling test - Wikipedia

   en.wikipedia.org/wiki/Anderson–Darling_test

   Anderson–Darling test. The Anderson–Darling test is a statistical test of whether a given sample of data is drawn from a given probability distribution. In its basic form, the test assumes that there are no parameters to be estimated in the distribution being tested, in which case the test and its set of critical values is distribution-free.