Analysis of Time Series Data
Gabriel Otieno Okello · 2022
Time series is an ordered sequence of values of a variable at equally spaced time intervals. Time series may be measured continuously or discretely. Time series data are data gathered collected sequentially over time on a given characteristic. A lag of time series is created when the time base is shifted by a given number of periods. Lags of a time series are often used as explanatory variables to model the actual time series itself. This is because the state of the few back time series periods may still has an influence on the series current state. The simple moving average of the time series can be used to estimate the trend component of a non-seasonal time series described by the additive model. Simple moving average is one of the averaging techniques for “smoothing out” the irregular fluctuations in the time series data. Exponential smoothing can be used to make short-term forecasts for time series data.