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Using a friendly, non-technical approach, the second edition of 'Regression Basics' introduces readers to the fundamentals of regression. Accessible to anyone with an introductory statistics background, this book builds from a simple two-variable model to a model of greater complexity. Author Leo H. Kahane weaves four engaging examples throughout the text to illustrate not only the techniques of regression but also how this empirical tool can be applied in creative ways to consider a broad array of topics.

Regression analysis.

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Regression analysis

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"This book provides a concise treatment of statistical regression modelling together with three detailed case studies for undergraduate students and professional master students with limited background in calculus. All sections have been retained from the second edition, with the author clarifying sections and reworking the more challenging topics. The author has added more end-of-chapter exercises and has added coverage of several new topics. All methods are clearly illustrated using datasets that are available in a variety of formats on the book's supplemental website. Detailed instructions for applying the methods are provided for many software packages, including SPSS, Minitab, DataDesk, SAS, JMP, R, Eviews, Stata, Statistica, and Excel.The book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, Bayesian modeling, and time series and forecasting.The writing is clear and careful, avoiding overly technical language. There is extensive cross-referencing, an exhaustive index, an appendix with all notation and formulas collected together, a mathematics refresher, a list of references, and a glossary of terms. Illustrations, graphs, and computer software output appears throughout. Detailed exercises collected together at the end of each chapter are carefully chosen to illustrate concepts and aid understanding. Brief solutions for half of the exercises are provided in an appendix while complete solutions to all the exercises are available in an Instructor's Manual. Supplemental exercises are available on the book's website. In addition, Instructor and student resources are available on the book's website, including datasets, software information, presentation slides, supplemental exercises, and videos covering particular topics and software demonstrations"--

Regression analysis. --- Statistics.

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This work introduces general strategies for testing interactions in logistic regression as well as providing the tools to interpret and understand the meaning of coefficients in equations with product terms.

Logistic regression analysis.

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The focus in this second edition is on logistic regression models for individual level (but aggregate or grouped) data. Multiple cases for each possible combination of values of the predictors are considered in detail.

Regression analysis. --- Logistic distribution.