What type of data might include stock prices and weather forecasts?

The correct choice is sequential data because stock prices and weather forecasts both exhibit patterns over time. Sequential data refers to information that is organized in a temporal order, allowing for analysis of trends and changes that occur from one moment to the next.

In the case of stock prices, they fluctuate based on various market conditions and can be analyzed to observe trends or predict future movements. Similarly, weather forecasts use historical data to predict future weather conditions, tracking changes over time.

Both stock prices and weather forecasts are valuable for time series analysis, which takes advantage of the sequential nature of this type of data to inform decision-making and predictions. Consequently, they align with the characteristics of sequential data, which inherently focuses on the importance of the order and timing of events.