in statistical inference analysis. In such analysis, decisions are based entirely on the analysis of data collected through a random sampling of the total population.
5S. P. Shao, Mathematics and Quantitative Methods, 3rd ed. (Cincinnati: South Western Publishing Company, 1986), 217.
7L. J. Kazmier, Business Statistics, 3rd ed. (New York: McGraw Hill Book Company, 1986), 1.
The principal techniques of statistical inference are interval estimation and hypothesis testing. Although statistical inference techniques are directly concerned with estimating values or with the testing of hypotheses concerning population parameters, the results of these procedures are related to alternative courses of action or to alternative decisions. As an example, the acceptance of a null hypothesis (or the inabil ity to reject a null hypothesis) in statistical inference analysis which indicated that the sales level for a product will be below the breakeven point for that product would, also, typically be associated with a decision not to market the product.
Perhaps the most important use of statistics and statisti cal procedures to the administrator and manager is that of testing hypotheses. This procedure is one which permits the making of inferences.8
THE APPLICATION OF LINEAR REGRESSION PROCEDURESIN TESTING HYPOTHESES
There are several statistical procedures which are used in the testing of hypotheses. Three procedures which are widely used by administrators and managers are (1) analysis of variance (ANOVA), (2) linear regression analysis, and (3) cor relation analysis. Correlation analysis requires the applica tion of linear regression procedures.
Analysis of variance is a "statistical technique that assesses the effects of one or more categorical independent variables (factors), measured at any level upon a continuous dependent variable that is usually assumed to be measured at an interval level."9 In other words,...