advantages and disadvantages of linear model communication
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Oh, isn't that just a happy little question! Linear models are like a trusty paintbrush in your art kit - they're simple, easy to interpret, and great for making predictions. Plus, they can help you understand relationships between variables in a clear and straightforward way. Just remember, every model has its own unique charm, so it's all about finding the right one for your creative journey.
For a linear I can see no advantage in the table method.
when does it make sense to choose a linear function to model a set of data
It made significantly better predictions of planetary positions in our sky.
It offered more natural explanation for the apparent retrograde motion of planets in our sky.
LinearIn a linear model, the plotted data follows a straight line. Every data point may not fall on the line, but a line best approximates the overall shape of the data. You can describe every linear model with an equation of the following form:y = mx + bIn this equation, the letter "m" describes the angle, or "slope," of the line. The "x" describes any chosen value on the horizontal axis, while the "y" describes the number on the vertical axis that corresponds to the chosen "x" value.QuadraticIn a quadratic model, the data best fits a different type of curve that mathematicians call quadratic. Quadratic models have a curved shape that resembles the letter "u." You can describe all quadratic models with an equation of the form:Y = ax^2 + bx + cAs with linear models, the "x" corresponds to a chosen value on the horizontal axis and "y" gives the correlating value on the vertical axis. The letters "a," "b" and "c" represent any number, i.e., they will vary from equation to equation