Regression/correlation analysis and time series analyses and their applications

Regression analysis is concerned with estimation of “the value of a [dependent] variable Y corresponding to a given value of an [independent] variable X” whose values can be obtained from sample data thus infer the relatedness – or correlation – of the two variables (Spiegel & Stephens, 2008, p. 321). In business, regression can be used in aspects such as sales to find how the level of promotion activities have increased sales volumes or in production to find how increased working periods – overtime – has affected output. Often, data can be arranged according to time – seconds, minutes, hours, and years – resulting into a time series graph with the “regression line or curve [of the graph being referred to ] trend line or trend curve” (Spiegel & Stephens, 2008, p. 321). Time series and regression models are important tools for forecasting, estimation or prediction of such business aspects as demand, material requirements and sales.

Reference

Spiegel, M. R. & Stephens, L. J. (2008). Schaum’s outlines of: Theory and problems of statistics (4th Ed.). New York: McGraw-Hill Companies, Inc

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