WPC 300 Final Exam Business Analytics 2026 – 200 Questions on ETL, Regression, Machine Learning & Data Analysis Exam

This document contains approximately 200 exam-style questions with verified answers based on comprehensive business analytics concepts, aligned with Bulletproof Problem Solving by Charles Conn & Robert McLean and core data analytics coursework. It provides in-depth coverage of analytics frameworks, statistical analysis, regression models, machine learning, ETL processes, and database management. The material is structured in a detailed Q&A format to support both conceptual understanding and final exam preparation. As shown in the document (pages 1–3), foundational topics include the agile analytics process (starting with business discovery), ETL workflows (loading into data warehouses), and the four key types of analytics: descriptive, explanatory, predictive, and prescriptive. Early sections also include real-world applications such as using descriptive analytics to analyze past sales data and predictive analytics to forecast future demand. Mid-sections (pages 4–10) provide strong coverage of statistics and data analysis, including measures of central tendency (mean, median, mode), dispersion (variance, standard deviation), hypothesis testing (p-values, Type I error, confidence levels), and regression analysis (R-squared, multicollinearity, residuals). The document also explores classification models such as logistic regression, confusion matrices, and probability-based predictions for decision-making scenarios. Later sections (pages 10–19) focus on advanced analytics and data science topics including clustering (k-means, hierarchical), supervised vs unsupervised learning, artificial intelligence, deep learning, and real-world applications such as spam filtering and customer behavior prediction. Additional coverage includes database concepts (SQL queries, primary keys, referential integrity), ETL architecture, A/B testing, experimental design, and cognitive biases (anchoring, bandwagon, overconfidence), ensuring full alignment with WPC 300 final exam expectations. This resource is ideal for students enrolled in WPC 300 or similar Business Analytics, Data Science, or Decision Analytics courses. It is suitable for courses such as Business Analytics, Statistics for Business, Machine Learning Fundamentals, Database Management, and Decision Sciences. Additionally, it benefits business students, data analysts, and professionals seeking a comprehensive review of analytics concepts, statistical modeling, and data-driven decision-making for final exams and practical applications. Keywords: WPC 300 final exam questions, business analytics comprehensive review, ETL process data warehouse, descriptive predictive prescriptive analytics, regression analysis R squared multicollinearity, logistic regression classification confusion matrix, hypothesis testing p value type 1 error, clustering k means hierarchical, supervised unsupervised machine learning, artificial intelligence deep learning basics, SQL queries inner join primary key, referential integrity database systems, A B testing experimental design, decision making biases anchoring bandwagon, statistics mean median mode variance