Forecasting Module 1 By Sue B. Schou Phone:

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Presentation transcript:

Forecasting Module 1 By Sue B. Schou Phone: 208-282-4608 Email: schosue@isu.edu

Learning Objectives Identify the time series components in a graph Make a time series graph using Minitab

What is a time series? Time series data is collected in equally spaced, consecutive time periods. Examples: Quarterly data Monthly data Annual data Daily data

Entering data in Minitab Time series data is entered in a single column with the data in time sequence order. When forecasting, usually there will be only one variable of interest such as revenue, sales, etc; hence, the single column in Minitab.

Example: Time Series Data for Greeting Card Sales Qtr1 Qtr2 Qtr3 Qtr4 222 339 336 878 443 413 398 1143 695 698 737 1647 Data is collected in time sequence order.

Example in Minitab

Time Series Plots Time series components are identified by examining a graph of the data. A graph of time series data is called a time series plot in Minitab. The x-axis must always have the time variable while the y-axis has the variable of interest.

Vocabulary To develop an adequate forecast, one must be able to identify the four time series components in the data: 1)_trend__

Trend “Overall upward or downward tendency of the data” Weiers, 2005, p.798

Example of Upward Trend

Quiz Time Which of the graphs below shows trend?

Quiz Time Answer The graph below shows upward trend. The graph below is described as stationary since it has no trend.

Vocabulary To develop an adequate forecast, one must be able to identify the four time series components in the data: 1)_Trend_________ 2)_Seasonality_____

Seasonality “Variation in a time series due to periodic fluctuations that repeat over a period of one year or less” Weiers, 2005, p. 798

Example of Seasonality

Quiz Time Which of the graphs below show seasonality?

Quiz Time Answer This graph shows seasonality – note the high every year. This graph shows trend but no seasonality.

Vocabulary To develop an adequate forecast, one must be able to identify the four time series components in the data: 1)_Trend______ 2)_Seasonality__ 3)_Cyclical_____

Cyclical Variation in a time series sequence due to economic factors such as recession or growth; occurs over longer periods of time than a year Not easily predicted

Example of Cyclical Data

Vocabulary To develop an adequate forecast, one must be able to identify the four time series components in the data: 1)__Trend________ 2)__Seasonality____ 3)__Cyclical_______ 4)__Erratic________

Erratic/Irregular Random fluctuations due to chance Not predictable Outliers in the data would be an example of the erratic component

Example of Erratic Data

Quiz Time Name the time series components in this graph.

Quiz Time Answer All four time series components are present: upward trend, seasonality (notice the pattern every four quarters; low in the first quarter, high in the fourth quarter), cyclical (go back to the cyclical example (the data used is close to the same), and erratic (outlier—oil embargo in 1977 created a slump in retail sales).

Seasonality Sometimes seasonality is not easily detected by examining the time series graph. Alternative methods: 1) Do decomposition in Minitab and examine the graph of the seasonal indices. 2)Examine the list of seasonal indices.

Seasonality Note that seasonality is not easily detected in this graph.

Seasonality continued The graph of the seasonal indices shows the pattern in the data over the 12 months most revenue: May least revenue: June

Seasonality continued Another alternative is to examine the seasonal indices. If the seasonal indices are all close to 1 (at the thousandths place), then there is no seasonality. If the seasonal indices fluctuate about 1 at the tenths or hundredths place, then there is seasonality.

Seasonality continued Period Index 1 1.21028 2 0.91178 3 0.97219 4 0.87616 5 1.51585 6 0.49611 7 1.34893 8 1.04286 9 1.08254 10 0.59272 11 0.79806 12 1.15252 No seasonality Period Index 1 1.00168 2 0.99930 3 0.99354 4 1.00548 Notice fluctuation is occurring at the thousandths place only and all numbers are exceedingly close to 1.

Using Minitab The directions for making a time series plot are available in two forms: 1) view the video clip here and/or 2) print the step-by-step directions available under handouts