ABSTRACT
A time series is an ordered sequence of observations. Although the ordering is usually through time, particularly in terms of some equally spaced intervals, the ordering may be taken through other dimensions, such as space. Agricultural time series analyses and forecasting could be applied to annual crop yields or the prices of produce with regard to their seasonal variations. The number of influenza outbreaks in successive weeks during the winter season could be approached as a time series problem by an epidemiologist. The chapter describes some of the simple techniques that will detect the main characteristics of a time series. The most important objectives of time series analysis are to forecast the future values of the series. Once a good time series model has become available, it can be used to make inferences about future observations. Even with good time series models the reliability of the forecast is based on the assumption that the future behaves like the past.
