A time series dataset is a collection of data points collected or recorded at specific time intervals. These datasets are often used to track changes over time, such as daily stock prices, monthly sales figures, or yearly temperature averages. The key feature of time series data is that the observations are ordered chronologically, allowing for analysis of trends, seasonal patterns, and potential forecasting. Time series analysis involves various techniques to understand and predict future values based on historical data. Common methods include moving averages, exponential smoothing, and ARIMA models. These techniques help identify patterns and make informed decisions in fields like finance, economics, and environmental science.