👉 In statistical analysis, a nonstationary process refers to a set of data where there is no predictable trend or pattern. This means that the values in the dataset are not necessarily stationary, meaning they do not follow a linear relationship with time. Nonstationary processes can arise from various sources such as random noise, sampling error, and other types of errors. In statistical analysis, nonstationary processes are often used to identify outliers, which are points in a dataset that are far away from the rest
