In a naive forecast, the forecast is equal to:

• A. The average of all prior observations
• B. The last observed value
• C. The weighted mean of recent data
• D. The median of the data set

Answer: (B)

The main idea is that a naive forecast uses the most recent observed value as the forecast for the next period. This simple rule assumes there’s no expected change from one moment to the next, so the best guess is just what was just observed. It serves as a straightforward baseline to judge more complex forecasting methods.

Why this fits: the next value is predicted to be the same as the last observed value, capturing the idea of no immediate shift in the level.

Why the other options don’t fit: averaging all prior observations would set the forecast to the overall mean, which smooths over recent changes and ignores the current level. A weighted mean of recent data is a smoother that emphasizes newer periods but still isn’t simply copying the last value. The median focuses on a central value of the data set, which isn’t a forecast for the next point in a time series.

So the forecast equals the last observed value.