STA100: Industrial Statistics, SQC and SPC

The STA100 course covers industrial statistics, statistical quality control (SQC), and statistical process control (SPC). It teaches engineers, technicians, and supervisors to apply modern statistical methods to analyze process and plant data, improving quality and control.

This course is ideal for process engineers, research engineers, laboratory personnel, analyzer technicians, instrument engineers, and supervisors who want to enhance their understanding of statistical tools and methods for process improvement.

The STA100 course is available entirely online and can be completed in 6 hours, offering a convenient learning option for busy professionals.

No prerequisites are required. The course is designed for individuals at all levels, from beginners to those looking to enhance their statistical knowledge.

You will learn how to apply statistical methods to real plant data, interpret results using tools like histograms, scatter plots, regression analysis, and implement statistical process control (SPC) and Six Sigma practices.

The course covers descriptive statistics, histograms, Pareto charts, T-tests, F-tests, ANOVA, regression analysis, control charts, capability indices, CUSUM and EWMA charts, and more.

This course will improve your ability to analyze, interpret, and present process data, helping you use statistical tools to monitor and improve process control, ultimately enhancing plant performance and customer satisfaction.

Topics include descriptive statistics, statistical process control (SPC), hypothesis testing, regression analysis, capability indices, time series analysis, experimental design, product reliability, and gauge studies.

The course teaches how to identify real process problems and apply statistical methods such as control charts and regression analysis to monitor and improve processes, ensuring higher efficiency and better quality control.

SPC is a method used to monitor and control a process through statistical analysis. It is vital for maintaining product quality, reducing variability, and ensuring consistent process performance in industrial settings.

The course covers key aspects of Six Sigma, including statistical methods for process improvement, and helps participants understand how to use statistical tools to drive Six Sigma initiatives and achieve operational excellence.

These indices measure a process's ability to meet specifications. The STA100 course teaches you how to calculate and interpret these indices to assess process performance and identify areas for improvement.

Yes, the course includes detailed lessons on control charts such as X and mR charts, CUSUM, and EWMA, which are essential for monitoring and controlling processes effectively in a variety of industries.

The course covers reliability analysis methods, including failure modes, the Weibull distribution, and warranty periods, helping you predict and manage product lifetimes and improve the design and durability of systems.

You will learn about various experimental design techniques, including Taguchi methods, factorial designs, and response surface methodology (RSM), to optimize process and product performance based on statistical analysis.

Yes. STA100 empowers you to convert raw data into actionable insights—whether it’s identifying sources of variability, determining root causes, or validating improvements.

Absolutely. The course is structured around real plant use cases and provides practical templates, workflows, and examples that can be implemented right after the training.

STA100 teaches the data literacy and statistical thinking needed to work with smart sensors, real-time analytics, and predictive quality systems in modern manufacturing environments.

Yes. Statistical methods taught in STA100 support ISO, FDA, and customer quality audits by ensuring you can demonstrate process capability, consistency, and data-driven control.

Very much so. QA/QC professionals will benefit from understanding process behavior, control limits, measurement system analysis, and defect analysis methods like Pareto and capability studies.

STA100 focuses on applied industrial statistics. It moves beyond theory to show how statistical tools are used specifically in process control, plant operations, and quality management settings.

Yes. Upon successful completion, participants receive a PiControl Solutions certificate, which can be added to professional profiles or submitted for PDH/CEU credits (subject to local approval).

Yes. With prior approval, attendees can bring anonymized plant data for discussion or troubleshooting during the course, making the experience even more relevant and hands-on.