Explaining the things you need to know in order to read empirical papers in the social and health sciences, as well as techniques needed to build personal statistical models, this user-friendly volume includes background material on study design, bivariate regression, and matrix algebra. To develop technique, Freedman also includes computer labs, with sample computer programs, and illustrates the principles and pitfalls of modeling. The book is rich in exercises with answers. Target audiences include undergraduates and beginning graduate students in statistics, as well as students and professionals in the social and health sciences.

1.Obsevational studies and experiments 2.The regression line 3.Matrix algebra 4.Multiple regression 5.Path models 6.Maximum likelihood 7.The bootstrap 8.Simultaneous equations

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