STQM Exam Q&A (100+ Questions) | Sampling, Probability, Chebyshev, Normal Distribution | Statistics & Technology in Quality Management

This document contains over 100 solved questions with verified A+ answers for the STQM (Statistics and Technology in Quality Management) exam, carefully structured for the 2025/2026 academic year. The content is focused on statistical analysis, data interpretation, and probability theory—all framed within quality management applications. It’s a complete exam prep resource that covers both conceptual theory and applied mathematical problem-solving. Covered topics include: Data & Variables Identifying quantitative vs. qualitative data Understanding variables, individuals in a study, and types of data measurement levels (nominal, ordinal, interval, ratio) Sampling & Survey Design Techniques: Stratified, Cluster, Systematic, and Convenience Sampling Concepts of population vs. sample, census vs. sampling, and random digit selection Descriptive Statistics 5-number summaries, range, mean, median, standard deviation, IQR Coefficient of variation, trimmed mean, and analysis of skewed distributions Probability & Distributions Chebyshev's Theorem, percentiles, empirical rule, and binomial distributions Use of z-scores, standard normal distribution, and area-based calculations under the curve Calculating P(E), P(E^c), compound probabilities, and Venn diagram applications Combinatorics & Applied Math Permutations, combinations, outfit and license plate generation problems Real-world probability modeling like acceptance sampling in manufacturing (e.g. defective chip batches) Interpretation of expected value, standard deviation, and probability thresholds Regression & Prediction Simple linear regression formula development Using regression to predict outcomes and understand residuals vs. extrapolation/interpolation This document is best suited for: Students in Statistics, Quality Assurance, Engineering Management, or Business Analytics programs Learners preparing for SQA STQM exams, internal assessments, or certification courses in data-driven quality management Instructors, tutors, or lecturers seeking a well-structured, numerically validated question bank Keywords: STQM, statistics for quality management, probability, Chebyshev's theorem, normal distribution, standard deviation, 5-number summary, regression, linear prediction, binomial distribution, z-scores, sampling techniques, data types, coefficient of variation, trimmed mean, skewness, survey methods, acceptance sampling, combinatorics, population mean, standard normal