ABSTRACT
Time series data is a series of observations on values that a variable takes at different points in time, such as hourly, daily, weekly, monthly, yearly, etc. Time series analysis, discussed in Chapter 5, is useful to uncover patterns in the sequence of numbers, such as trend, seasonality, or cycles, or to forecast future patterns. For instance, some service providers present different total sales figures depending on the month or season. Identifying these outlines can be helpful to manage inventories, personnel, working hours, and so on. Chapter 5 presents the steps to identify the data pattern, followed by guidance to choose the suitable model and how to perform the forecast analysis. The techniques are illustrated with theoretical description, followed by an example with the SPSS commands and the results tables with comments. The chapter also includes exercises, such as a road map to perform the analysis, an interpretative exercise with results tables, and a market context to guide a research design.
