Linear refers to the graph line. If the line on the graph is a straight line, then the plots/relationship that make up that line are linear. Conversely, if the line is anything other than linear (such as any kind or curve...parabola, hyperbola, etc), then the relationship is said to be non-linear.
For example, if you graph the following sets of (X,Y) coordinates, you will get a straight line that slopes upward to the right: (1,1), (2,2), (3,3), etc. But the following set of (X,Y) coordinates will produce a line that curves: (1,1), (2,3), (3,5).
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A linear relationship is a connection between two variables that can be represented by a straight line on a graph. In this type of relationship, as one variable changes, the other changes at a constant rate. The equation for a linear relationship is typically in the form y = mx + b, where m is the slope of the line and b is the y-intercept.
A Linear relationship is a relationship where variable quantities are proportional with each other.
A vector plane is a two-dimensional space defined by a set of two non-parallel vectors. It represents all linear combinations of these vectors. In linear algebra, vector planes are used to visualize and understand relationships between vectors in space.
A transistor can function in both linear and non-linear modes. In the linear mode, it can amplify small signals with a linear relationship between input and output. In the non-linear mode, the transistor operates as a switch, turning on or off based on the input signal.
The sigma matrix, also known as the covariance matrix, is important in linear algebra because it represents the relationships between variables in a dataset. It is used to calculate the variance and covariance of the variables, which helps in understanding the spread and correlation of the data. In mathematical computations, the sigma matrix is used in various operations such as calculating eigenvalues and eigenvectors, performing transformations, and solving systems of linear equations.
Linear momentum is conserved in a closed system when there are no external forces acting on it. This means that the total linear momentum of the system before an event is equal to the total linear momentum after the event.
The Maxwell model derivation is performed by combining the spring and dashpot elements in series to represent the viscoelastic behavior of a material. The model is derived by analyzing the stress and strain relationships in the system and applying the principles of linear viscoelasticity.