Description: Negative correlation is a statistical concept that describes an inverse relationship between two variables. In this type of correlation, when one variable increases, the other tends to decrease, and vice versa. This phenomenon is commonly represented by a correlation coefficient that ranges from -1 to 0, where -1 indicates a perfect negative correlation. Negative correlation is fundamental in data science and statistics, as it allows analysts to identify patterns and relationships in datasets. For example, in various types of analysis, it might be observed that as one variable increases, another one decreases, suggesting a negative correlation. This relationship is crucial for making informed decisions in various fields, such as economics, health, and marketing. Additionally, in anomaly detection using artificial intelligence, identifying negative correlations can help highlight unusual or unexpected behaviors in the data, allowing analysts to act quickly on potential issues or opportunities.
