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  2. Quantitative analysis (chemistry) - Wikipedia

    en.wikipedia.org/wiki/Quantitative_analysis...

    The general expression Qualitative Analysis [...] refers to analyses in which substances are identified or classified on the basis of their chemical or physical properties, such as chemical reactivity, solubility, molecular weight, melting point, radioactivity properties (emission, absorption), mass spectra, nuclear half-life, etc. Quantitative Analysis refers to analyses in which the amount ...

  3. Qualitative comparative analysis - Wikipedia

    en.wikipedia.org/wiki/Qualitative_comparative...

    The small N problem arises when the number of units of analysis (e.g. countries) available is inherently limited. For example: a study where countries are the unit of analysis is limited in that are only a limited number of countries in the world (less than 200), less than necessary for some (probabilistic) statistical techniques.

  4. Parameter space - Wikipedia

    en.wikipedia.org/wiki/Parameter_space

    A simple model of health deterioration after developing lung cancer could include the two parameters gender [2] and smoker/non-smoker, in which case the parameter space is the following set of four possibilities: {(Male, Smoker), (Male, Non-smoker), (Female, Smoker), (Female, Non-smoker)} .

  5. Mixture model - Wikipedia

    en.wikipedia.org/wiki/Mixture_model

    A typical finite-dimensional mixture model is a hierarchical model consisting of the following components: . N random variables that are observed, each distributed according to a mixture of K components, with the components belonging to the same parametric family of distributions (e.g., all normal, all Zipfian, etc.) but with different parameters

  6. Parametric statistics - Wikipedia

    en.wikipedia.org/wiki/Parametric_statistics

    Parametric statistical methods are used to compute the 2.33 value above, given 99 independent observations from the same normal distribution. A non-parametric estimate of the same thing is the maximum of the first 99 scores. We don't need to assume anything about the distribution of test scores to reason that before we gave the test it was ...

  7. Principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Principal_component_analysis

    Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.

  8. College football award winners: Full list of winners for 2024 ...

    www.aol.com/college-football-award-winners-full...

    We're firmly in awards season with the 2024 college football regular season and conference championships complete.. While the 2024 Heisman Trophy will be awarded on Saturday, the nation's top ...

  9. Principal component regression - Wikipedia

    en.wikipedia.org/wiki/Principal_component_regression

    In statistics, principal component regression (PCR) is a regression analysis technique that is based on principal component analysis (PCA). PCR is a form of reduced rank regression . [ 1 ] More specifically, PCR is used for estimating the unknown regression coefficients in a standard linear regression model .