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  2. Oversampling and undersampling in data analysis - Wikipedia

    en.wikipedia.org/wiki/Oversampling_and_under...

    If we were designing a survey to gather data, we would survey 4 times as many females as males, so that in the final sample, both genders will be represented equally. (See also Stratified Sampling.) Under-representation of one class in the outcome (dependent) variable.

  3. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1] Data is collected and analyzed to answer questions, test hypotheses, or disprove theories. [11] Statistician John Tukey, defined data analysis in 1961, as:

  4. Synthetic data - Wikipedia

    en.wikipedia.org/wiki/Synthetic_data

    Synthetic data is generated to meet specific needs or certain conditions that may not be found in the original, real data. One of the hurdles in applying up-to-date machine learning approaches for complex scientific tasks is the scarcity of labeled data, a gap effectively bridged by the use of synthetic data, which closely replicates real experimental data. [3]

  5. Statistical classification - Wikipedia

    en.wikipedia.org/wiki/Statistical_classification

    Algorithms of this nature use statistical inference to find the best class for a given instance. Unlike other algorithms, which simply output a "best" class, probabilistic algorithms output a probability of the instance being a member of each of the possible classes. The best class is normally then selected as the one with the highest probability.

  6. Statistics - Wikipedia

    en.wikipedia.org/wiki/Statistics

    A typical "Business Statistics" course is intended for business majors, and covers [71] descriptive statistics (collection, description, analysis, and summary of data), probability (typically the binomial and normal distributions), test of hypotheses and confidence intervals, linear regression, and correlation; (follow-on) courses may include ...

  7. Data transformation (statistics) - Wikipedia

    en.wikipedia.org/wiki/Data_transformation...

    If data generated by a random vector X are observed as vectors X i of observations with covariance matrix Σ, a linear transformation can be used to decorrelate the data. To do this, the Cholesky decomposition is used to express Σ = A A'. Then the transformed vector Y i = A −1 X i has the identity matrix as its covariance matrix.

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  9. Statistical inference - Wikipedia

    en.wikipedia.org/wiki/Statistical_inference

    Statistical inference makes propositions about a population, using data drawn from the population with some form of sampling.Given a hypothesis about a population, for which we wish to draw inferences, statistical inference consists of (first) selecting a statistical model of the process that generates the data and (second) deducing propositions from the model.