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Pearson correlation coefficient
Statistical measure that quantifies the strength and direction of the linear relationship between two continuous quantitative variables, ranging from -1 to +1.
Chi-square test
Non-parametric statistical test used to assess the independence between two qualitative variables by comparing observed frequencies to theoretical frequencies.
Scatter plot
Graphical visualization representing pairs of values from two quantitative variables where each point corresponds to an individual observation.
Covariance
Statistical measure indicating how two variables vary together, positive if they move in the same direction and negative if they move in opposite directions.
Correlation matrix
Square table presenting correlation coefficients between all pairs of variables in a dataset, facilitating the identification of multivariate relationships.
Spearman correlation test
Non-parametric test measuring the strength and direction of the monotonic relationship between two variables based on their ranks rather than their raw values.
Contingency table
Matrix crossing the frequency occurrences of two qualitative variables to analyze their association and detect dependencies.
Student's t-test for two samples
Statistical test comparing the means of two groups to determine if the observed difference is statistically significant.
Coefficient of determination R²
Indicator measuring the proportion of variance of the dependent variable explained by the regression model, ranging from 0 to 1.
Residual analysis
Systematic examination of the differences between observed values and values predicted by a model to validate its fundamental assumptions.
Regression line
Linear fitting line that minimizes the sum of squared residuals to best represent the relationship between two quantitative variables.
Fisher's test
Statistical test comparing the variances of two populations or evaluating the overall significance of a regression model.
Partial correlation coefficient
Measure of the relationship between two variables after controlling for the effect of one or more additional variables.
Kendall's test
Non-parametric test assessing the concordance between the ranks of two variables, particularly robust to extreme values.
Bivariate box plot
Visualization combining boxplots of two variables to simultaneously compare their distributions and detect relational patterns.
Elasticity
Measure of the percentage change in one variable in response to a 1% change in another variable, essential in economic analysis.