When a time series appears to approximately have consistent percentage differences from observation to observation, the appropriate model to fit is the:

A. quadratic trend.
B. linear trend.
C. exponential trend.
D. ARIMA.

Suppose you take a measure for each 5 seconds in a given observation, and the thing you are observing seems to change in the same amount in each meassure. This may mean that you are observing a linear relationship of the form y = a*x + b

Then, the simpler way to study this data set is by fiting with a linear equation.

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When a time series appears to approximately have consistent percentage differences from observation to observation, the appropriate model to fit is the: A. quadratic trend. B. linear trend. C. exponential trend. D. ARIMA.

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When a time series appears to approximately have consistent percentage differences from observation to observation, the appropriate model to fit is the:

A. quadratic trend.
B. linear trend.
C. exponential trend.
D. ARIMA.