If we fit a linear trend to data that are growing exponentially, A. the fitted trend will be too high at the end B. the forecasts, if extrapolated, will be too low C. the forecasts, if ...
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... extrapolated, will be too high D. the fitted trend will be too low in the middle
Linear least squares regression is by far the most widely used modeling method. It is what most people mean when they say they have used "regression", "linear regression" or "least squares" to fit a ...
(Continued below)
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User: If we fit a linear trend to data that are growing exponentially, A. the fitted trend will be too high at the end B. the forecasts, if extrapolated, will be too low C. the forecasts, if extrapolated, will be too high D. the fitted trend will be too low in the middle

Weegy: Linear least squares regression is by far the most widely used modeling method. It is what most people mean when they say they have used "regression", "linear regression" or "least squares" to fit a model to their data. [ [ Not only is linear least squares regression the most widely used modeling method, but it has been adapted to a broad range of situations that are outside its direct scope. ] ]

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