Which of the following forecasting methods is not suitable for time series data that exhibits a horizontal pattern?

The correct choice highlights a method that is inappropriate for forecasting when the data exhibits a horizontal pattern. Linear trend regression is designed to identify and project trends over time, which includes increasing or decreasing patterns within the data. When time series data displays a horizontal pattern, it indicates that the data points fluctuate around a constant mean without any apparent trend.

In such cases, methods that are specifically tailored to address stable or fluctuating data without trend components, such as moving averages, exponential smoothing, or naive forecasting, would be more suitable. These techniques are effective in uncovering the average or smoothing out irregularities in the data without imposing a trend, aligning well with horizontal patterns. Linear trend regression, on the other hand, attempts to fit a line that represents a continuous upward or downward movement, making it ineffective for horizontal data. Therefore, using linear trend regression in this context is not advisable.