If two variables are not independent of each other, it means that the occurrence or value of one variable affects or is related to the occurrence or value of the other variable. In statistical terms, this implies that knowing the value of one variable provides information about the other, indicating a potential correlation or causal relationship between them. This lack of independence can manifest in various forms, such as positive or negative correlations, and is important to consider in data analysis and hypothesis testing.
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