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Researchers in the social sciences business policy studies and other areas rely heavily on the use of linear regression analysis. This manual provides the background needed to understand much of the empirical work relying on linear regression analysis; it explains its basic procedures and terms. Written at an elementary level and assuming only a minimal mathematics background this book focuses on the intuitive and verbal interpretation of regression coefficients associated statistics and hypothesis tests. The manual also explains the terminology often encountered in the literature such as standardized regression coefficients dummy variables interaction terms and transformations. This book can be used as a text in a variety of courses in different disciplines. Examples are drawn from demography economics education finance marketing policy analysis political science public administration and sociology. This manual does not substitute for a statisics course; it does not teach the use of regression analysis. Rather it is intended to fill the void that exists when a student studies empirical papers before taking a statistics course. However the volumes level does make it suitable as a supplementary text for a statistics course. Chapters cover linear regression multiple linear regression hypothesis testing extensions to multiple regression models and problems and issues in linear regression. Appendices contain derivation of a and b critical values for a t distribution regression output from SAS and SPSS and suggested texts.