There are several occasions when we might try to observe and capture an event at different points in time. Often, we would end up drawing a correlation or association between adjacent observations that cannot be handled by an approach that deals with data that is independent and identically distributed. The approach that takes all of this into consideration in a mathematical and statistical manner is called time series analysis.

Time series analysis has been used in a number of fields, such as the automotive, banking, and retail industries, product development, and so on. There is no boundary for its use, and so analysts and data scientists are exploring this area to the hilt in order to derive the maximum benefit for organizations.

In this section, we will go through a few of the concepts around time series analysis that will lay the foundation for a deeper understanding in the future. Once we have established this foundation, we will jump into modeling.