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  2. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    Users can transform or summarize data by applying arbitrary functions. [4]: 132 Since Pandas is built on top of NumPy, all NumPy functions work on Series and DataFrames as well. [9]: 115 Pandas also includes built-in operations for arithmetic, string manipulation, and summary statistics such as mean, median, and standard deviation.

  3. Kernel density estimation - Wikipedia

    en.wikipedia.org/wiki/Kernel_density_estimation

    Kernel density estimation of 100 normally distributed random numbers using different smoothing bandwidths.. In statistics, kernel density estimation (KDE) is the application of kernel smoothing for probability density estimation, i.e., a non-parametric method to estimate the probability density function of a random variable based on kernels as weights.

  4. List of statistical software - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_software

    SmartPLS – statistics package used in partial least squares path modeling (PLS) and PLS-based structural equation modeling SOCR – online tools for teaching statistics and probability theory Speakeasy (computational environment) – numerical computational environment and programming language with many statistical and econometric analysis ...

  5. Bootstrapping (statistics) - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping_(statistics)

    GPR is a Bayesian non-linear regression method. A Gaussian process (GP) is a collection of random variables, any finite number of which have a joint Gaussian (normal) distribution. A GP is defined by a mean function and a covariance function, which specify the mean vectors and covariance matrices for each finite collection of the random variables.

  6. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    Tukey promoted the use of five number summary of numerical data—the two extremes (maximum and minimum), the median, and the quartiles—because these median and quartiles, being functions of the empirical distribution are defined for all distributions, unlike the mean and standard deviation.

  7. List of fields of application of statistics - Wikipedia

    en.wikipedia.org/wiki/List_of_fields_of...

    Forensic statistics is the application of probability models and statistical techniques to scientific evidence, such as DNA evidence, and the law. In contrast to "everyday" statistics, to not engender bias or unduly draw conclusions, forensic statisticians report likelihoods as likelihood ratios (LR).

  8. Marginal distribution - Wikipedia

    en.wikipedia.org/wiki/Marginal_distribution

    In probability theory and statistics, the marginal distribution of a subset of a collection of random variables is the probability distribution of the variables contained in the subset. It gives the probabilities of various values of the variables in the subset without reference to the values of the other variables.

  9. Clamp (function) - Wikipedia

    en.wikipedia.org/wiki/Clamp_(function)

    Although spreadsheets like Excel, Open Office Calc, or Google Sheets don't provide a clamping function directly, the same effect can be achieved by using functions like MAX & MIN together, by MEDIAN, [8] [9] or with cell function macros. [10] When attempting to do a clamp where the input is an array, other methods must be used. [11]