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  2. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    In statistics, the 68–95–99.7 rule, also known as the empirical rule, and sometimes abbreviated 3sr or 3 σ, is a shorthand used to remember the percentage of values that lie within an interval estimate in a normal distribution: approximately 68%, 95%, and 99.7% of the values lie within one, two, and three standard deviations of the mean ...

  3. Credible interval - Wikipedia

    en.wikipedia.org/wiki/Credible_interval

    For the case of a single parameter and data that can be summarised in a single sufficient statistic, it can be shown that the credible interval and the confidence interval coincide if the unknown parameter is a location parameter (i.e. the forward probability function has the form (|) = ()), with a prior that is a uniform flat distribution; [6 ...

  4. Confidence and prediction bands - Wikipedia

    en.wikipedia.org/wiki/Confidence_and_prediction...

    Confidence bands can be constructed around estimates of the empirical distribution function.Simple theory allows the construction of point-wise confidence intervals, but it is also possible to construct a simultaneous confidence band for the cumulative distribution function as a whole by inverting the Kolmogorov-Smirnov test, or by using non-parametric likelihood methods.

  5. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    4.2 Confidence intervals. ... the values less than one standard deviation from the mean account for 68.27% of the set; while two standard deviations from the mean ...

  6. Prediction interval - Wikipedia

    en.wikipedia.org/wiki/Prediction_interval

    Given a sample from a normal distribution, whose parameters are unknown, it is possible to give prediction intervals in the frequentist sense, i.e., an interval [a, b] based on statistics of the sample such that on repeated experiments, X n+1 falls in the interval the desired percentage of the time; one may call these "predictive confidence intervals".

  7. Confidence interval - Wikipedia

    en.wikipedia.org/wiki/Confidence_interval

    The colored lines are 50% confidence intervals for the mean, μ. At the center of each interval is the sample mean, marked with a diamond. The blue intervals contain the population mean, and the red ones do not. In statistics, a confidence interval (CI) is a tool for estimating a parameter, such as the mean of a population. [1]

  8. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    A basic example is given by prediction intervals: For the normal distribution, the interval [, +] contains approximately two thirds (68%) of the probability (or of a large sample), and [, +] contain 95%.

  9. Student's t-distribution - Wikipedia

    en.wikipedia.org/wiki/Student's_t-distribution

    Calculating the confidence interval. Let's say we have a sample with size 11, sample mean 10, and sample variance 2. For 90% confidence with 10 degrees of freedom, the one-sided t value from the table is 1.372 . Then with confidence interval calculated from