To determine which function best fits the data from a scatterplot, you would typically analyze the shape and trend of the data points.
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Linear Functions: Functions of the form \(y = mx + b\) (like \(y = 4x + 8\), \(y = 100x + 2\), and \(y = 2x + 5\)) represent a straight line. If the scatterplot shows a linear trend, one of these functions may fit.
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Exponential Function: The function \(y = 4^x + 8\) represents an exponential growth curve. If the scatterplot shows rapid growth, this might be a fit.
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Quadratic Function: The function \(y = 20x^2 + 10\) represents a parabolic curve. If the scatterplot resembles a U-shape or an inverted U-shape, this might be the best fit.
Without seeing the actual scatterplot, you would select the function based on the observed trend. If the data points rise and fall in a parabolic shape, then the quadratic function might be the best fit. If they trend upwards in a straight line, a linear function is better. For an exponential trend, you would choose the exponential function.
If you could describe the shape or pattern of the data from the scatterplot, I could help you make a better-informed choice.