Multiple Regression: A PrimerSAGE Publications, 29 Ara 1998 - 224 sayfa Presenting topics in the form of questions and answers, this popular supplemental text offers a brief introduction on multiple regression on a conceptual level. Author Paul D. Allison answers the most essential questions (such as how to read and interpret multiple regression tables and how to critique multiple regression results) in the early chapters, and then tackles the less important ones (for instance, those arising from multicollinearity) in the later chapters. With this organization, readers can stop at the end of any chapter and still feel like they′ve already gotten the meat of the subject. |
Diğer baskılar - Tümünü görüntüle
Sık kullanılan terimler ve kelime öbekleri
additional analysis approximations assumptions average better calculate called causal Chapter coefficient column conclude correlation deleted dependent described discussed dummy variables effect equation errors estimates exactly example factor Figure function give groups highly hypothesis important income increase independent variables individual intercept interpret less linear look married mean measured method multicollinearity multiple regression names nonlinear observed omitted packages points possible predicted probability problem produce programs questions random reason regression analysis regression coefficients regression equation regression line regression model relationship reported represent residuals sample scale schooling scores shows simple slope social standard standard deviation standard error statistically significant status Suppose Table tell term there’s things tolerance transformation true usually variance violations zero