Which of the following describes time series data?

Time series data refers to a set of observations collected sequentially over time, allowing for analysis of trends, cycles, and potential seasonal variations. This type of data is particularly valuable in various fields such as economics, finance, and environmental studies where understanding changes over time is crucial.

When data is collected over several time periods, it enables analysts to track and analyze patterns, such as how a variable increases or decreases over weeks, months, or years. This longitudinal aspect helps in forecasting future values based on historical performance. Thus, time series data captures the dynamics of change, making it possible to recognize and interpret trends effectively.

Other options describe different types of data: data collected at a single point in time refers to cross-sectional data, which does not provide insights into changes over time. Data related to multiple subjects suggests a broader observational study but doesn’t indicate the time-oriented nature of the data. Random sampling of data refers to a method of selecting a sample from a population but does not specifically pertain to the time aspect that characterizes time series data.