Time Series Analysis

In its most simple form, time series analysis is the organization of data over specific time intervals in order to both evaluate and predict data in the set. By keeping time as the independent variable, it is helpful for tracking features such as trends, variability, and seasonality. One important aspect of time series analysis is its flexibility. You can produce different models using classification (assigning data into categories), curve fitting (using a curve to analyze relationships between variables), descriptive analysis (identifying patterns like trends/cycles), segmentation (splitting data to reveal properties), and more. Time series has many applications including forecasting trends in weather, economics, and even earthquakes.