Trend Analysis
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This research provides a critique of trend analysis. Trend analysis is one approach to time series projection.1 Time series projection may be as uncomplicated as the projec tion of an unadjusted trend, or it may be based upon more sophisticated adjustments for seasonal and cyclical patterns.2 In either case, or in some middle ground case, such as the application of least squares curve fitting (regression) to time series data, to project future values of a variable, a future trend is projected.3 The primary concern of this research, however, is basic trend analysis, which includes (1) arithmetic trend, (2) moving average trend, (3) exponential smoothing, and (4) exponential trend.4 One so called middle ground approach to trend analysis the application of least squares curve fit ting (regression) to time series data is also considered, because of its wide use in conjunction with each of the four approaches to trend projection indicated above.5 Regression 1J. L. Pappas, and E. F. Brigham, Fundamentals of Manager ial Economics, 3rd ed. (Chicago: The Dryden Press, 1989), 138. 2J. J. McAuley, Economic Forecasting for Business (Engle wood Cliffs, New Jersey: Prentice Hall, Inc., 1986), 10 31. 3R. J. Tersine, Production/Operations Management, 3rd ed. (New York: North Holland Publishing, 1990), 431 433. 4G. W. Summers, W. S. Peters, and C. P. Armstrong, Basic Statistics in Business and Economics, 5th ed. (Belmont, Cali fornia: Wadsworth Publi
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between a dependent and independent variable, using all prior values of the variables.
Simple regression analysis involves the analysis of the relationship between one dependent variable and one explana tory, or independent, variable. Multiple regression, on the other hand, is a general statistical technique through which
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10S. G. Makridakis, Forecasting, Planning, and Strategy for the 21st Century (New York: The Free Press, 1990), 70 71.
one can analyze the relationship between a dependent or criter ion variable and a set of independent or predictor variables. Multiple regression may be viewed either as a descriptive tool by which the linear dependence of one variable on others is summarized and decomposed, or as an inferential tool by which the relationships in the population are evaluated from the examination of sample data.
Multiple regression is used as a descriptive tool in three types of situations, as follows: (1) to develop a self weight ing estimating equation by which to predict values for a dependent variable; (2) to control for confounding variables so as to better evaluate the contribution of other variables; and (3) to test explicit causal theories. Multiple regression is used as an infere
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Some common words found in the essay are:
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Approximate Word count = 2372
Approximate Pages = 9 (250 words per page)
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