Which of the following is NOT a time-series model?

• A. Multiple regression
• B. Exponential smoothing
• C. Naive approach
• D. Moving averages

Answer: (A)

Time-series models are used to analyze data points collected or recorded at specific time intervals to identify trends, patterns, or seasonal variations over time. Evaluating the options, multiple regression does not fall under the category of time-series models because it focuses on the relationship between a dependent variable and one or more independent variables, which may or may not be time-related.

On the other hand, exponential smoothing, the naive approach, and moving averages are all time-series forecasting methods. Exponential smoothing gives more weight to recent observations, while the naive approach uses the most recent observation as the forecast for the next period. Moving averages involve averaging a set number of past observations to make future predictions. These methods are specifically designed to work with time-ordered data and are classified as time-series models, making multiple regression the only option that does not fit this category.