
Pearson Correlation Coefficient
Pearson Correlation Coefficient is a statistical measure that evaluates the linear relationship between two continuous variables. It measures the strength and direction of the relationship between the two variables, where a value of +1 indicates a perfect positive correlation, a value of -1 indicates a perfect negative correlation, and a value of 0 indicates no correlation. The Pearson Correlation Coefficient is widely used in data science and machine learning for feature selection, data preprocessing, and model evaluation. It is also used to identify patterns and relationships between variables in exploratory data analysis. The Pearson Correlation Coefficient assumes that the variables are normally distributed and have a linear relationship. It is sensitive to outliers and can be affected by the scale of the variables.
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