Linear Segmentation

Linear segmentation is a method used in data analysis to break down continuous datasets into distinct, non-overlapping segments based on specific criteria. This technique is especially valuable in identifying trends, patterns, and changes within large sets of data.

Key Concepts:

• Breaking a dataset into smaller, manageable segments.
• Each segment represents a unique portion of the data with its own characteristics.
• Linear models are typically used to define boundaries between segments.

Process Overview:

1. Collect data for analysis.
2. Apply a linear model to identify potential segmentation points.
3. Validate the segments to ensure meaningful distinctions.

"Linear segmentation is powerful in identifying shifts in data patterns, allowing for targeted interventions or analyses."

Example of Data Segmentation: