Relationships

In Data Science, relationships refer to the connections or associations between variables in a dataset. These relationships can be either linear or non-linear and can be positive or negative. Understanding the relationships between variables is crucial in data analysis as it helps in identifying patterns, making predictions, and drawing insights. Correlation and regression analysis are some of the statistical techniques used to measure the strength and direction of relationships between variables. In machine learning, relationships between variables are used to build predictive models that can be used to make accurate predictions on new data.
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