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  2. Weibull distribution - Wikipedia

    en.wikipedia.org/wiki/Weibull_distribution

    In probability theory and statistics, the Weibull distribution / ˈ w aɪ b ʊ l / is a continuous probability distribution. It models a broad range of random variables, largely in the nature of a time to failure or time between events. Examples are maximum one-day rainfalls and the time a user spends on a web page.

  3. Statistics - Wikipedia

    en.wikipedia.org/wiki/Statistics

    In business, "statistics" is a widely used management-and decision support tool. It is particularly applied in financial management, marketing management, and production, services and operations management. [69] [70] Statistics is also heavily used in management accounting and auditing.

  4. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    Sample size determination or estimation is the act of choosing the number of observations or replicates to include in a statistical sample.The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample.

  5. Statistic - Wikipedia

    en.wikipedia.org/wiki/Statistic

    There are a variety of functions that are used to calculate statistics. Some include: Sample mean, sample median, and sample mode; Sample variance and sample standard deviation; Sample quantiles besides the median, e.g., quartiles and percentiles; Test statistics, such as t-statistic, chi-squared statistic, f statistic

  6. Estimating equations - Wikipedia

    en.wikipedia.org/wiki/Estimating_equations

    In statistics, the method of estimating equations is a way of specifying how the parameters of a statistical model should be estimated. This can be thought of as a generalisation of many classical methods—the method of moments , least squares , and maximum likelihood —as well as some recent methods like M-estimators .

  7. Standard deviation - Wikipedia

    en.wikipedia.org/wiki/Standard_deviation

    Example of samples from two populations with the same mean but different standard deviations. Red population has mean 100 and SD 10; blue population has mean 100 and SD 50. A large standard deviation indicates that the data points can spread far from the mean and a small standard deviation indicates that they are clustered closely around the mean.