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  2. Joint probability distribution - Wikipedia

    en.wikipedia.org/wiki/Joint_probability_distribution

    Moreover, the final row and the final column give the marginal probability distribution for A and the marginal probability distribution for B respectively. For example, for A the first of these cells gives the sum of the probabilities for A being red, regardless of which possibility for B in the column above the cell occurs, as ⁠ 2 / 3 ⁠.

  3. pandas (software) - Wikipedia

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

    Subsets of data can be selected by column name, index, or Boolean expressions. For example, df[df['col1'] > 5] will return all rows in the DataFrame df for which the value of the column col1 exceeds 5. [4]: 126–128 Data can be grouped together by a column value, as in df['col1'].groupby(df['col2']), or by a function which is applied to the index.

  4. Marginal distribution - Wikipedia

    en.wikipedia.org/wiki/Marginal_distribution

    For example, suppose P(L = red) = 0.2, P(L = yellow) = 0.1, and P(L = green) = 0.7. Multiplying each column in the conditional distribution by the probability of that column occurring results in the joint probability distribution of H and L, given in the central 2×3 block of entries. (Note that the cells in this 2×3 block add up to 1).

  5. Probability distribution fitting - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution...

    The numerical method may consist of assuming a range of p values, then applying the distribution fitting procedure repeatedly for all the assumed p values, and finally selecting the value of p for which the sum of squares of deviations of calculated probabilities from measured frequencies (chi squared) is minimum, as is done in CumFreq.

  6. Factorial experiment - Wikipedia

    en.wikipedia.org/wiki/Factorial_experiment

    The last four column vectors belong to the A × B interaction, as their entries depend on the values of both factors, and as all four columns are orthogonal to the columns for A and B. The latter can be verified by taking dot products. A 2 × 2 × 2 experiment: This will have 1 degree of freedom for every main effect and interaction. For ...

  7. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    The column space of a matrix is the image or range of the corresponding matrix transformation. Let be a field. The column space of an m × n matrix with components from is a linear subspace of the m-space. The dimension of the column space is called the rank of the matrix and is at most min(m, n). [1]

  8. Data-driven programming - Wikipedia

    en.wikipedia.org/wiki/Data-driven_programming

    The condition/action model is also similar to aspect-oriented programming, where when a join point (condition) is reached, a pointcut (action) is executed. A similar paradigm is used in some tracing frameworks such as DTrace , where one lists probes (instrumentation points) and associated actions, which execute when the condition is satisfied.

  9. Main effect - Wikipedia

    en.wikipedia.org/wiki/Main_effect

    A factor averaged over all other levels of the effects of other factors is termed as main effect (also known as marginal effect). The contrast of a factor between levels over all levels of other factors is the main effect.