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WPC 300 Business Analytics & Problem Solving 2026 – 150 Questions on Statistics, Logic Trees & Decision Making Exam

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This document contains approximately 150 exam-style questions with verified answers based on business analytics and structured problem-solving concepts, aligned with Bulletproof Problem Solving by Charles Conn & Robert McLean and foundational statistics materials. It provides comprehensive and in-depth coverage of logic trees, statistical analysis, hypothesis testing, data visualization, and decision-making frameworks used in modern business environments. The content is structured in a detailed Q&A format to support both conceptual understanding and exam-focused preparation. As shown in the document (pages 1–3), foundational topics include the seven-step bulletproof problem-solving process (define, disaggregate, prioritize, workplan, analyze, synthesize, communicate), the 5 Whys root cause technique, and SMART goal setting. Early sections also introduce key analytical frameworks such as MECE logic trees, pruning techniques, and decision trees. For example, page 2 highlights that 68% of data lies within one standard deviation in a normal distribution, while page 3 explains inductive vs deductive logic trees and Six Sigma tools like DMAIC and PDSA. Mid-sections (pages 6–12) provide strong coverage of statistics and data analysis, including data types (nominal, ordinal, interval, ratio), distributions (normal, Poisson, binomial), hypothesis testing (Z-test, t-test, ANOVA), and key metrics such as p-values, significance levels, and Type I/II errors. The document also explores advanced analytical techniques such as regression, Bayesian analysis, Monte Carlo simulation, and A/B testing. Later sections (pages 13–20) focus on business applications including machine learning basics, data visualization (bar charts, scatter plots, histograms), decision-making biases (anchoring, salience, endowment effect), and strategic tools like game theory, Pareto principle, and sensitivity analysis. This resource is ideal for students enrolled in WPC 300 or similar Business Analytics, Data Science, or Decision-Making courses. It is suitable for courses such as Business Analytics, Statistics for Business, Operations Management, and Data-Driven Decision Making. Additionally, it benefits business students, analysts, consultants, and professionals seeking to strengthen their analytical thinking, statistical reasoning, and structured problem-solving skills for exams and real-world applications. Keywords: WPC 300 exam questions, business analytics statistics, bulletproof problem solving steps, logic trees MECE pruning decision tree, hypothesis testing z test t test anova, normal distribution 68 95 99.7 rule, poisson binomial distribution, regression analysis correlation r squared, p value significance level type 1 type 2 error, monte carlo simulation business, bayesian analysis conditional probability, data visualization charts histogram scatter plot, decision making biases anchoring salience endowment, pareto principle 80 20 rule, sensitivity analysis what if

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WPC 300 2026 Exam Questions
and Verified Answers | Already
Graded A+


What step of the bullet proof problem solving helps avoid making common

decision-making biases? - 🧠ANSWER ✔✔Step 4: Build a work plan and

time table


Primary focus of managerial skills in 1970's - 🧠ANSWER ✔✔Focus on

strategy


Problem solving technique used for prioritization - 🧠ANSWER ✔✔Pruning

,Steps of Bullet Proof Problem Solving - 🧠ANSWER ✔✔Define problem,

Disaggregate, Prioritize, workplan, analyze, synthesize, communicate


Five Whys Technique - 🧠ANSWER ✔✔A form of root cause analysis

popularized at Toyota where the question "why?" is asked five successive

times, each time looking one level deeper at the underlying problem

Probability of an observation that lies bt range of -1 < x < 1. Between one

standard deviations in a normal distribution - 🧠ANSWER ✔✔68%


2 standard deviations - 🧠ANSWER ✔✔95% of data


3 standard deviations - 🧠ANSWER ✔✔99.7% of data


SMART goals - 🧠ANSWER ✔✔Specific, Measurable, Attainable, Realistic,

Timely


Logic trees should be - 🧠ANSWER ✔✔mutually exclusive and collectively

exhaustive


Pruning process - 🧠ANSWER ✔✔remove the elements that are only a

minor influence


Multidimension Analysis: Slicing - 🧠ANSWER ✔✔Keep one dimesion

constant and analysing two dimensions of a cube

, Poiison Distribution applied for - 🧠ANSWER ✔✔Discrete random variable


Measures in multi-dimensional - 🧠ANSWER ✔✔Revenue, quantity, cost of

goods sold


Inductive logic tree - 🧠ANSWER ✔✔subelements on the left and problem

statements on the far right


Deductive logic tree - 🧠ANSWER ✔✔subelements on the right and the

problem statement on the far left


Good problem statements - 🧠ANSWER ✔✔address decision-maker's

values, structured to allow sufficient scope for creativity, specific and

measureable


PDSA - 🧠ANSWER ✔✔Plan, Do, Study, Act


DMAIC - 🧠ANSWER ✔✔Core tool in six sigma project. Used to improve

processes and quality


Design thinking - 🧠ANSWER ✔✔ID need, empathize, define, ideate

(brainstorm), form hypothesis, build, prototype, deliver


Problem Worksheet - 🧠ANSWER ✔✔-Problem statement




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