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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書目名稱Linear Models in Matrix Form影響因子(影響力)學科排名




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書目名稱Linear Models in Matrix Form網(wǎng)絡(luò)公開度學科排名




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書目名稱Linear Models in Matrix Form讀者反饋學科排名

中古

Jonathon D. BrownComprehensively covers use of linear models in matrix form.Utilizes R and open source spreadsheets as standard tools for algebraic calculations.Many examples and full-color screenshots data files to h

半圓鑿

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Common-Migraine

Simple Linear Regression,Chapter 1 introduced you to a variety of matrix properties and operations. Among other things, you learned how to use the determinant and inverse of a matrix to solve equations with unknown quantities. In the remainder of this book, you will use these operations to perform a wide variety of statistical analyses.

dyspareunia

lavish

Analysis of Covariance,In Chaps. . and ., we learned that multiple regression can be used to analyze data with categorical predictors. In the next three chapters, we will extend our coverage to include designs that combine categorical and continuous predictors.

Creatinine-Test

Cross-Product Terms and Interactions,n of a criterion holding all other variables constant. Because the coefficients are statistically independent, a one-unit change in .. predicts a .. change in . across all levels of ... This . (as it is called) is demanded by the form of an ordinary linear regression model:

Benign

Factorial Designs,lso be used with designs that combine two or more categorical predictors. In most cases, the categorical variables are crossed to form a factorial design. In this chapter, you will learn how to use multiple regression to analyze and interpret factorial designs.

細微的差異

978-3-319-34569-7Springer International Publishing Switzerland 2014

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