Forecasting Demand Using Time Series Data A time series is a time-ordered sequence of observations taken at regular intervals over a period of time (hourly, daily, weekly, monthly, quarterly, annually, etc.). The data may be measurements of demand, earnings, profits, shipments, accidents, output, precipitation, productivity, CPI, etc. Analysis of time series requires the analyst to identify the underlying behavior of the series. The can often be accomplished by plotting the data and visually examining the plot. One or more patterns might appear: trends, seasonal variations, cycles, irregular variation, and random variations. Typical components of a time series are (1) the trends, (2) seasonal variations, (3) cyclical variation, (4) irregular variations, and (5) random variations of pure noise. 1-(800) flowers is in the business of selling flowers. Briefly describe the components of a time series and explain how these components impact the volume of flower sales