Titlebook: Linear Models in Matrix Form; A Hands-On Approach Jonathon D. Brown Textbook 2014 Springer International Publishing Switzerland 2014 Compu

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Problematic Observations, a more detailed discussion. Table 6.1 organizes them into three categories of increasing importance. The first category refers to properties that are desirable but not required; the second refers to properties that are required when ordinary least squares (OLS) estimation is used to find a least sq

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Errors and Residuals,random variables, with mean 0 and variance ..:.We discussed the normality assumption in Chap. ., learning ways to determine whether the errors are normally distributed (e.g., QQ plot, Jarque-Bera test) and the steps we can take to normalize them if they are not (e.g., Box-Cox transformation). In thi

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ARC

Categorical Predictors,ences between levels are qualitative (either-or) rather than quantitative (more or less). Examples include subject variables (male, female), affiliations (Democrat, Republican, Libertarian), or an experimental treatment (control group vs. experimental group). Historically, analysis of variance (ANOV

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Mediation,want to know why they are related; by what causal mechanism does one variable affect another? Unfortunately, the search for causes is fraught with difficulty. As the Scottish philosopher David Hume noted more than 250 years ago, causes are always inferred, never observed. For this reason, causal ass

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Textbook 2014ced topics are easy to follow through analyses that were performed on an open-source spreadsheet using a few built-in functions. These topics include ordinary linear regression, as well as maximum likelihood estimation, matrix decompositions, nonparametric smoothers and penalized cubic splines. Each