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Jacob Cohen

    Frühling der Sayanim
    Applied multiple regression : correlation analysis for the behavioral sciences
    Statistical power analysis for the behavioral sciences
    Corporate Financial Reporting and Analysis
    • The authors chose the term 'global' for the book's title to convey the idea that the book is truly global in its coverage.  What distinguishes this book from others in financial accounting and corporate financial reporting is the seamless way it approaches the world's two dominant accounting regimes:  US Generally Accepted Accounting Principles (GAAP) and International Financial Reporting Standards (IFRS).  The tendency in the field is to present the material from a US GAAP perspective, with some discussion, usually at the end of the chapter, on financial reporting practices under IFRS and how they might differ from those of GAAP on the chapter topic.  Or, when the book is written from an IFRS perspective, US GAAP is ignored entirely.  The problem with this latter approach is that at least 40% of the world's total stock market capitalization is accounted for by companies reporting under US GAAP.  Meanwhile, more than half is accounted for by IFRS.  Investors in the global capital markets cannot neglect either of these two approaches.  The world will have one dominant accounting regime some day, but for the foreseeable future, we are left with two distinctive, though increasingly overlapping, sets of standards.  The challenge is to integrate these approaches in such a way that critical differences are addressed, but in a way that is accessible to the reader.

      Corporate Financial Reporting and Analysis
    • "Statistical Power Analysis" is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.

      Statistical power analysis for the behavioral sciences
    • The Applied Multiple Regression (LRM) model has been in use in statistical analyses for many years; but it was not until the late 1960's that a model was used to provide a multivariate analysis of the Katsulares/Mitri heart study data that its full power and applicability were totally appreciated. Since then the LRM model has become the standard method for regression analysis of dichotomous data in many fields, especially in the health sciences. This new and updated edition of the classic bestseller provides a focused introduction to the LRM model and its use in methods for modeling the relationship between a dichotomous outcome variable and a set of covariables

      Applied multiple regression : correlation analysis for the behavioral sciences