Quality Engineering Statistics (2026)

Descripción

• Are you familiar with basic statistical concepts, but feel like you never truly mastered them? • Have you tried to learn more advanced topics like probability distributions, hypothesis testing, or Design of Experiments (DOE), only to get lost in unnecessary jargon? • Would you rather perform real statistical analysis in Microsoft Excel instead of relying on expensive, specialized software? • And would you like to strengthen your analytical problem-solving skills to advance your career in quality, engineering, or manufacturing? If you answered “yes” to any of these questions, Quality Engineering Statistics (2026) was designed for you. This course proves that a strong foundation in quality statistics does not have to be difficult or "too theoretical" to learn. A Practical, Industry-Focused Statistics Course Quality Engineering Statistics (2026) is one of the most comprehensive statistics courses available on Udemy for manufacturing and quality professionals. With 170+ lectures and over 16 hours of instruction, the course covers the analytical tools you need to succeed in real industrial environments, not just on exams. Most statistical methods are demonstrated step-by-step in Microsoft Excel, and many lectures include downloadable Excel (.xls) templates you can immediately apply in your own work. The course content aligns with the Quantitative Methods and Tools section of the ASQ Certified Quality Engineer (CQE) Body of Knowledge (July 2022 edition), making it valuable both for professional development and certification preparation. Topics Covered A. Collecting and Summarizing Data • Types of data • Measurement scales • Data collection methods • Data accuracy and integrity • Data visualization techniques • Descriptive statistics • Graphical methods for depicting distributions B. Quantitative Concepts (All New for 2026) • Statistical terminology • Drawing statistical conclusions • Probability terms and concepts C. Probability Distributions • Continuous distributions • Discrete distributions D. Statistical Decision-Making • Point estimates and confidence intervals • Hypothesis testing • Paired-comparison tests • Goodness-of-fit tests • Analysis of variance (ANOVA) • Contingency tables E. Relationships Between Variables • Linear regression • Simple linear correlation • Time-series analysis F. Nonparametric Methods (All New for 2026) • Statistical inference and robustness • Testing sample means (Sign, Wilcoxon, Mann-Whitney tests) • Multiple random samples (Kruskal-Wallis and Friedman tests) • Correlation using Spearman’s rank test G. Statistical Process Control (SPC) • Objectives and benefits • Common and special causes • Variable selection • Rational subgrouping • Control charts • Control chart analysis • Short-run SPC H. Process and Performance Capability • Process capability studies • Process performance vs. specifications • Process capability indices • Process performance indices I. Design and Analysis of Experiments (DOE) • Terminology • Planning and organizing experiments • Experimental design principles • Full-factorial experiments • Two-level fractional factorial experiments Taught by Manufacturing Professionals, for Manufacturing Professionals This is far more than an exam-prep course. Quality Engineering Statistics (2026) is taught by two senior, manufacturing professionals who share dozens of real-world examples and case studies drawn from decades of experience in quality engineering, manufacturing, and operations. What You Get with This Course In addition to 16+ hours of video instruction, you receive: • Lifetime access to all course materials and all future updates • Dozens of Excel worksheets • 50 quiz questions, with 5–7 questions at the end of each section • Detailed practice problems throughout the course • Answer keys for all problem sets • Q&A access to the instructors through Udemy • Personalized Certificate of Completion What Students Say “This class is very comprehensive on the subject of statistics as it applies to the field of Quality Engineering. I don't remember a class consolidating all these topics into one package.” — William F. “One of the best courses I have seen on this topic.” — Willie C. “I graduated from Social Sciences and I am terrible at math… Now I am fully aware of how to use statistics, SPC, and how to successfully interpret the data.” — Erhan C. “One of the best Udemy courses I've ever attended! Well prepared and engaging instructors.” — Andrea T. Ready to Strengthen Your Statistical Skill Set? If you want to build confidence with data, make better decisions, and solve increasingly complex problems in the workplace, Quality Engineering Statistics (2026) will give you the tools to do exactly that. This course is designed to help you grow as a manufacturing quality professional ready for the next step in your career!

Lo que aprenderás

• Collecting and summarizing data including type of data, measurement scales, collection methods, visualization techniques, and descriptive statistics
• Statistics and probability terminology and concepts
• Statistical decision making including point estimates, confidence intervals, hypothesis testing, paired comparison tests, goodness of fit tests, ANOVA and more
• Tools for examining the relationships between variables such as linear regression, correlation, and time series analysis.
• Control charting: Objective and benefits, common and special causes, variable charts, attribute charts, interpreting the results, and short run SPC
• Process capability analysis: Pp, Ppk, Cp, Cpk, control limits, specification limits, and interpreting actual histograms and capability indices
• Design and analysis of experiments: Terminology, planning and organizing experiments, replication, balance, order and more; full and fractional factorial
• All topics in the "Quantitative Methods and Tools" section of the ASQ Certified Quality Engineer Body of Knowledge
• Introduction to nonparametric methods such as Sign Test, Wilcoxon Signed Rank, Spearman's Correlation, Kruskal Wallis Test, and more

Requisitos

• Basic understanding of manufacturing
• Basic math and spreadsheet skills