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  2. P–P plot - Wikipedia

    en.wikipedia.org/wiki/P–P_plot

    P–P plot. In statistics, a P–P plot (probabilityprobability plot or percent–percent plot or P value plot) is a probability plot for assessing how closely two data sets agree, or for assessing how closely a dataset fits a particular model. It works by plotting the two cumulative distribution functions against each other; if they are ...

  3. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    v. t. e. In probability theory and statistics, a probability distribution is the mathematical function that gives the probabilities of occurrence of possible outcomes for an experiment. [1][2] It is a mathematical description of a random phenomenon in terms of its sample space and the probabilities of events (subsets of the sample space). [3]

  4. Notation in probability and statistics - Wikipedia

    en.wikipedia.org/wiki/Notation_in_probability...

    Probability density functions (pdfs) and probability mass functions are denoted by lowercase letters, e.g. , or . Cumulative distribution functions (cdfs) are denoted by uppercase letters, e.g. , or . In particular, the pdf of the standard normal distribution is denoted by , and its cdf by .

  5. Probability plot correlation coefficient plot - Wikipedia

    en.wikipedia.org/wiki/Probability_plot...

    The probability plot correlation coefficient (PPCC) plot is a graphical technique for identifying the shape parameter for a distributional family that best describes the data set. This technique is appropriate for families, such as the Weibull, that are defined by a single shape parameter and location and scale parameters, and it is not ...

  6. Zero-inflated model - Wikipedia

    en.wikipedia.org/wiki/Zero-inflated_model

    Zero-inflated models are commonly used in the analysis of count data, such as the number of visits a patient makes to the emergency room in one year, or the number of fish caught in one day in one lake. [1] Count data can take values of 0, 1, 2, … (non-negative integer values). [2] Other examples of count data are the number of hits recorded ...

  7. Poisson distribution - Wikipedia

    en.wikipedia.org/wiki/Poisson_distribution

    The Poisson distribution is an appropriate model if the following assumptions are true: k is the number of times an event occurs in an interval and k can take values 0, 1, 2, ... . The occurrence of one event does not affect the probability that a second event will occur. That is, events occur independently.