University of Michigan - Ann Arbor

A time series is a set of measurements of a quantitative variable taken at sequential intervals over a continuous period of time. This approach allows researchers to track trends and ongoing changes within a specific domain, such as recording a factory's weekly worker productivity over an entire year.

Time Series

Time Series Analysis and Its Applications: With R Examples (Third edition)

A time series is a sequence of numerical data points in successive order. In investing, a time series tracks the movement of the chosen data points, such as a security’s price, over a specified period of time with data points recorded at regular intervals. There is no minimum or maximum amount of time that must be included, allowing the data to be gathered in a way that provides the information being sought by the investor or analyst examining the activity.

Time Series learning

An interrupted time-series design is a quasi-experimental approach and a variant of the pretest-posttest design. In this methodology, a researcher takes a time series—multiple measurements of a dependent variable at regular intervals—both before and after a treatment is introduced. The treatment effectively 'interrupts' the ongoing measurements. Unlike the simpler pretest-posttest design, which relies on a single before-and-after measurement, the inclusion of multiple measurements allows researchers to better distinguish the actual effect of the intervention from normal variation.

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