Regression Analysis 213 Success Secrets - 213 Most Asked Questions On Regression Analysis - What You Need To Know

Nonfiction, Reference & Language, Reference, Business & Finance

• Author: Beverly Puckett
• ISBN: 9781488539275
• Publisher: Emereo Publishing
• Publication: March 23, 2014
• Imprint: Emereo Publishing
• Language: English

In numbers, 'regression analysis' is a mathematical analytic procedure for approximating the connections amid factors. It contains numerous methods for depicting and examining some factors, once the center is on the connection amid a reliant changeable and one either further autonomous factors. More especially, reversion examination assists one comprehend in what way the distinctive worth of the reliant changeable (or 'Criterion Variable') amends once whatever one of the autonomous factors is diverse, when the other autonomous factors are held secured. Most normally, reversion examination approximates the provisional anticipation of the reliant changeable specified the autonomous factors – that is, the mean worth of the reliant changeable once the autonomous factors are secured.

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It contains 213 answers, much more than you can imagine; comprehensive answers and extensive details and references, with insights that have never before been offered in print. Get the information you need--fast! This all-embracing guide offers a thorough view of key knowledge and detailed insight. This Guide introduces what you want to know about Regression Analysis.

A quick look inside of some of the subjects covered: Predictions - Sports, Regression Analysis of Time Series, Poisson regression - Regression models, Randomized experiment - Statistical Interpretation, Artificial neural network - Real-life applications, Curve fitting, Accelerated failure time model - Model specification, Stepwise regression - Main approaches, Forecasting - Causal / econometric forecasting methods, Studentized residual, Estimation of covariance matrices, Memory improvement - Exercise, Polynomial regression - History, Outline of economics - General economic concepts, Bias-variance dilemma, Principal component regression, Data mining Background, K-nearest neighbors classification, and much more…