Predictive Power
Making Accurate Predictions from Data for Improved Decision Making
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Predictive Power
Narrated by:
Virtual Voice
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Narrated by:
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Virtual Voice
This title uses virtual voice narration
Virtual voice is computer-generated narration for audiobooks.
About this listen
The book invites you with an insightful chapter on Regression Analysis, tracing its historical background and the seismic impact it created on modern predictive models. Delving into the basics, it cleverly uses a narrative style to describe the concept of variables and their relationships, along with an enlightening introduction to prediction.
Unravel the concept of Simple Linear Regression, get acquainted with the interplay between dependent and independent variables, and master the method of least squares with this thorough guide. The eBook further propels you into the sphere of advanced linear regressions, offering information abound about Multiple and Nonparametric Regressions, and the art of interpreting Regression Coefficients.
Equip yourself with knowledge about validation and refinement techniques. Learn about R-Squared, Adjusted R-Squared, F-tests, t-tests, and techniques of combating overfitting and underfitting in the generous fifth chapter. Chapters six to eight guide you through practical steps of problem formulation, data acquisition and cleaning, collinearity, multicollinearity, and building regression models with the software.
The final chapters gesture towards exciting areas of application. Uncover the potent role of regression analysis in the world of business, such as marketing, supply chain management, and financial predictions. There are also chapters dwelling upon the important considerations of ethical consequences and bias in regression models. Last but not the least, get a glimpse into the pioneering future of regression analysis within machine learning, artificial intelligence, and the new era of data analysis.
Join us on this thrilling ride named "Predictive Power" − an eBook that stands as a doorway to the captivating world of regression analysis and predictive modeling, a skillset of the future, today.
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