This segment provides a clear explanation of linear time complexity (O(n)) in algorithms. It illustrates how different functions, despite having varying constants and coefficients, all fall under the O(n) category because the dominant factor is the linear relationship with the input size (n). The explanation effectively clarifies the concept by showing examples and highlighting the focus on the degree of the polynomial representing the time complexity. Time complexity classes: O(1) constant, O(log n) logarithmic, O(n) linear, O(n²) quadratic, O(n³) cubic, O(2ⁿ) exponential. Complexity is independent of constant factors.