Page 216 - DMGT404 RESEARCH_METHODOLOGY

Research Methodology

Notes and specifically,
y = 1.2085 + 0.3164(5) – 0.0443(5) 2
2000
= 1.68,

y = 1.2085 + 0.3164(6) – 0.0443(6) 2
2001
= 1.51

!

Caution Remember that the data set is small. Quarterly earnings per share figures for the
period may have been better because of the larger sample size. The significance test and
construction of the confidence interval is performed as previously shown. Furthermore,
as soon as new earnings per share figures become available, the regression line should be
recalculated, because there is always the chance that there may be a change in the
environment.

Self Assessment

Fill in the blanks:

1. Time series analysis is a ……………..forecasting tool.
2. In time series analysis, Each factor must be …………….and its effect ascertained upon
product sales.

3. A product’s seasonality is shown by the regularly recurring increases or decreases in sales
or production that are caused by ……………………….

10.2 Components of a Time Series

An observed value of a time series, Yt, is the net effect of many types of influences such as
changes in population, techniques of production, seasons, level of business activity, tastes and
habits, incidence of fire floods, etc. It may be noted here that different types of variables may be
affected by different types of factors, e.g., factors affecting the agricultural output may be entirely
different from the factors affecting industrial output. However, for the purpose of time series
analysis, various factors are classified into the following three general categories applicable to
any type of variable:

1. Secular Trend or Simply Trend
2. Periodic or Oscillatory Variations
(a) Seasonal Variations
(b) Cyclical Variations

3. Random or Irregular Variations

10.2.1 Secular Trend

Secular trend or simply trend is the general tendency of the data to increase or decrease or
stagnate over a long period of time. Most of the business and economic time series would reveal
a tendency to increase or to decrease over a number of years. For example, data regarding
industrial production, agricultural production, population, bank deposits, deficit financing, etc.,

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