WGU D208 Predictive Modeling – Task 1 Multiple Regression (NBM2) Performance Assessment Guide

WGU D208 Predictive Modeling – Task 1 Multiple Regression (NBM2) Performance Assessment GuideWGU D208 Predictive Modeling – Task 1 Multiple Regression (NBM2) Performance Assessment This comprehensive study guide and performance assessment document details Task 1: Multiple Regression for Predictive Modeling (NBM2 / PRFA) for Western Governors University’s Course D208 (Predictive Modeling). It outlines every requirement necessary to achieve full competency on WGU assessment rubrics. Key topics covered include formulating real-world organizational research questions, verifying multiple regression model assumptions, preparing continuous and categorical variables using Python or R, and conducting univariate and bivariate exploratory data visualizations.The document provides step-by-step instructions for constructing an initial regression model, implementing statistically based variable selection methods (such as AIC or p-value reduction), and analyzing reduced models alongside residual error plots. It also details coefficient interpretations, statistical and practical significance, business implications, and guidelines for delivering an effective Panopto video demonstration.Designed specifically for students in Data Analytics (MSDA / BSDA), Applied Statistics, or Computer Science, this document serves as a roadmap to navigating complex regression tasks, statistical modeling, and data-driven decision-making.WGU D208, Task 1 NBM2, Predictive Modeling, Multiple Regression, Python Regression Analysis, R Statistical Modeling, Residual Plot Analysis, Feature Selection, Model Reduction, MSDA WGU, PRFA D208, Data Analytics Assessment