Final answer:
Time series analysis is used for studying data that is collected over a period of time to identify trends and patterns, and is represented graphically through time series graphs. This kind of data is gathered sequentially over time and is distinct from cross-sectional data, which is collected at a single point in time.
Step-by-step explanation:
Time series analysis is used for studying data that is (b) Collected over a period of time. This type of analysis is important for identifying trends and patterns within data that has been collected sequentially over time intervals. Time series graphs are valuable tools that help in visualizing these trends, making it easier for researchers to draw insights from the data.
Unlike cross-sectional studies, which gather data from a sample at a single point in time, time series data captures the dynamics of the subject being studied over an extended period. This allows for a chronological order of data, which is essential for seeing how variables interact and change over time. For example, time series graphs can be used to track changes in the average temperature at a location throughout a month.
Time series data is not collected at random intervals nor is it collected from a single point in time as cross-sectional studies do. It is also different from data that might be collected from a random sample representing a larger population, which is often used in different types of statistical studies.