D.R.Anderson, D.J.Sweeney, T.A.Williams. Quantitative Methods for Business, South-
Western College Publishing, 11-th edition.
Components of a time series
Planning for the future
is an essential aspect of managing.
But for good planning we should make
How should we go about providing forecasts?
In this Lecture we discuss
Time Series Methods
(moving averages, weighted moving averages, and exponential smoothing),
Time series methods
discover a pattern in the historical data (time series) and then
this pattern into the future.
5.1 Components of a time series
is a set of observations of a variable measured at successive points in time or
over successive periods of time.
The pattern or behavior of the data in a time series has several components. The usual
assumption is that four separate components—
trend, cyclical, seasonal,
provide specific values for the time series.
In time series analysis, the measurements may be taken every hour, day, week, month, or year, or at
any other regular interval. Although time series data generally exhibit random fluctuations, the time
series may still show
gradual shifts or movements to relatively higher or lower values over a
longer period of time.
The gradual shifting of the time series over long period of time is referred to as the
in the time series.
This shifting or trend is usually the result of long- term factors such as changes in the population,
demographic characteristics of the population, technology, and consumer preferences.
, a manufacturer of photographic equipment may observe substantial month-to-month
variability in the number of cameras sold. However, in reviewing sales over the past 10 to 15 years,
this manufacturer may note a gradual increase in the annual sales volume. Suppose that the sales
volume was approximately 1700 cameras per month in 1996, 2300 cameras per month in 2001, and
2500 cameras per month in 2006. Although actual month-to-month sales volumes may vary
substantially, this gradual growth in sales shows an upward trend for the time series.