Lecture For Time Series And Forecasting

Topics: Time series analysis, Time, Term Pages: 11 (335 words) Published: April 4, 2015
TIME SERIES AND
FORECASTING
McGraw­Hill/Irwin

Copyright © 2010 by The McGraw­Hill Companies, Inc. All rights reserved.

Time Series and its
Components
TIME SERIES is a collection of data recorded over a period of time (weekly, monthly, quarterly), an analysis of history, that can be used by management to make current decisions and plans based on long-term forecasting. It usually assumes past pattern to continue into the future

Components of a Time Series
1.
2.

3.

4.

Secular Trend – the smooth long term direction of a time series Cyclical Variation – the rise and fall of a time series over periods longer than one year
Seasonal Variation – Patterns of change in a time series within a year which tends to repeat
each year
Irregular Variation – classified into:
Episodic – unpredictable but identifiable
Residual – also called chance fluctuation and unidentifiable

16-2

Secular Trend – Examples

16-3

Cyclical Variation – Sample
Chart

16-4

Seasonal Variation – Sample
Chart

16-5

Linear Trend Plot

16-6

The Moving Average
Method






16-7

Useful in smoothing time series to see its
trend
Basic method used in measuring
seasonal fluctuation
Applicable when time series follows fairly
linear trend that have definite rhythmic
pattern

Linear Trend Plot

16-8

Linear Trend


The long term trend of many business series
often approximates a straight line


Linear Trend Equation : Y a  bt
where :


Y  read "Y hat" , is the projected value of the Y
variable for a selected value of t
a  the Y - intercept
(estimated value of Y when t 0)
b the slope of the line
(average change in Y for each unit change in t )
t  any value of time (coded) that is selected
16-9

Linear Trend






16-10

Use Data Analysis-Regression analysis in
Excel to find the best linear relationship
between 2 variables: t and Y
Code time (t) and use it as the
independent variable
E.g. let t be 1 for the first year, 2 for the
second, and so on (if data are annual)

11

16-11

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