Advanced and Multivariate Statistical Methods : Practical Application and Interpretation

Ideal for non-math majors, __Advanced and Multivariate Statistical Methods__ teaches students to interpret, present, and write up results for each statistical technique without overemphasizing advanced math. This highly applied approach covers the why, what, when and how of advanced and multivariate statistics in a way that is neither too technical nor too mathematical. Students also learn how to compute each technique using SPSS software. **New to the Sixth Edition** * Instructor ancillaries are now available with the sixth edition. * All SPSS directions and screenshots have been updated to Version 23 of the software. * Student learning objectives have been added as a means for students to target their learning and for instructors to focus their instruction. * Key words are reviewed and reinforced in the end of chapter material to ensure that students understand the vocabulary of advanced and multivariate statistics. Steps for Screening Grouped Data; Steps for Screening Ungrouped Data; Exercises for Chapter 3; Chapter 4 Factorial Analysis of Variance; I. Univariate Analysis of Variance; II. Factorial Analysis of Variance; Section 4.1 Practical View; Purpose; Sample Research Questions; Section 4.2 Assumptions and Limitations; Methods of Testing Assumptions; Section 4.3 Process and Logic; The Logic Behind Factorial ANOVA; Interpretation of Results; Writing Up Results; Section 4.4 Sample Study and Analysis; Problem; Methods and SPSS "How To"; Output and Interpretation of Results "Ideal for non-math majors, Advanced and Multivariate Statistical Methods teaches students to interpret, present, and write up results for each statistical technique without overemphasizing advanced math. This highly applied approach covers the why, what, when and how of advanced and multivariate statistics in a way that is neither too technical nor too mathematical. Students also learn how to compute each technique using SPSS software." -- From Amazon Introduction to multivariate statistics -- A guide to multivariate techniques -- Pre-analysis data screening -- Factorial analysis of variance -- Analysis of covariance -- Multivariate analysis of variance and covariance -- Multiple regression -- Path analysis -- Factor analysis -- Discriminant analysis -- Logistic regression