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Introduction to data visualization and characterization -- Random vectors and the multivariate normal distribution -- Explaining covariance structure : principal components -- Linear model for numerical and categorical response variables -- Linear mixed effects model -- Diagnosis of variation...
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1. Introduction 2 -- Start using Gretl and R 3 -- Basic Material 4 -- Hypothesis testing 5 -- Simple linear regression … 6 -- Multiple regression 7 -- Regression using dummy variables 8 -- Non linear models 9 -- Time series analysis 10 …-technical approach, the book covers topics including simple regression and hypothesis testing, multiple regression with control variables …
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"Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Use machine learning to understand your customers, frame decisions, and drive value The business analytics...
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