Use single exponential smoothing to smooth the data in a time series, and to provide short-term forecasts. For example, you might want to predict the temperatures for the next 7 days using the data in a time series containing successive temperatures in a city over the past 50 days. Or you might want to predict the sales of a certain brand of cereals in a supermarket over the next 6 months using the sales data collected over 3 years (36 months).

Use single exponential smoothing when:

·    You have data with no or a slowly evolving trend.

·    Your data has no seasonal pattern.

·    The series has no missing values.

·    You want short-term forecasts.

This procedure also serves as a general smoothing method.

You wish to predict employment of women over the next six months in a segment of the food industry using data collected over the past sixty months. You also counted the number of restaurants considered for each month.

Data: Employment.MTW (available in the Sample Data folder).