This repo contains a Time Series Decomposition and Analysis on the Forza User data.

Data available at : https://steamdb.info/charts/

A time-series data is a series of data points or observations recorded at different or regular time intervals. In general, a time series is a sequence of data points taken at equally spaced time intervals. The frequency of recorded data points may be hourly, daily, weekly, monthly, quarterly or annually.

Time-Series Forecasting is the process of using a statistical model to predict future values of a time-series based on past results.

1. Trend - The trend shows a general direction of the time series data over a long period of time. A trend can be increasing(upward), decreasing(downward), or horizontal(stationary).
2. Seasonality - The seasonality component exhibits a trend that repeats with respect to timing, direction, and magnitude. Some examples include an increase in water consumption in summer due to hot weather conditions.
3. Cyclical Component - These are the trends with no set repetition over a particular period of time. A cycle refers to the period of ups and downs, booms and slums of a time series, mostly observed in business cycles. These cycles do not exhibit a seasonal variation but generally occur over a time period of 3 to 12 years depending on the nature of the time series.
4. Irregular Variation - These are the fluctuations in the time series data which become evident when trend and cyclical variations are removed. These variations are unpredictable, erratic, and may or may not be random.
5. ETS Decomposition - ETS Decomposition is used to separate different components of a time series. The term ETS stands for Error, Trend and Seasonality.