Time series analysis is the analysis of data that varies with time.
Examples are earthquake seismograms, climate records, temperature records, etc.
It is the job of time series analysis to recover the maximum amount of information contained in the data. When analyzing time series data, various artifacts and distortions need to be understood and minimized. The fact that the data is taken over a finite length of time limits the precision with which the frequencies that make up the signal can be determined. This is very important when you want to separate out two signals that are nearly the same frequency. In addition, the presence of offsets and trends in the data can introduce distortion of the results.