Exsilon Data & Statistical Solutions





		CURRICULUM Introduction to MINITAB & Basic Data Analysis – 2.5 days, $1250 Statistical Analysis for Process Improvement using MINITAB – 2.5 days, $1250 Design and Analysis of Experiments using MINITAB – 2.5 days, $1250 FREE COACHING AND SUPPORT Exsilon wants you to feel empowered to apply what you have learned to your specific projects after you return to your business, so we will assign you a statistical coach. Your coach will be available to you for up to four hours of one-on-one support free of charge. Our aim is to aid you in learning the best ways to evolve your processes using MINITAB to achieve your goals. Introduction to MINITAB and Basic Data Analysis – 2.5 days, $1250 including four hours of free coaching and support In this course Exsilon will showcase the principles of statistical process control (SPC) and capability analysis from basic tools to more advanced techniques, not currently taught in the standard quality improvement programs. You will see how to select the right control chart and capability analysis for specific challenges, avoid the common mistakes many practitioners make, and model processes that you previously thought too complex. You will learn how to incorporate statistical thinking and problem solving into your process improvement initiatives by using simple graphical and numerical techniques to evaluate and characterize process performance and discover causes for process variability. And because Exsilon teaches without bias, we will highlight the strengths and weaknesses of MINITAB to illustrate how best to use the application In addition you will: learn how to share data between MINITAB and Excel learn how to use MINITAB’s tools to manipulate and restructure data to prepare for analysis learn to evaluate processes to desired targets and required specifications learn how and where MINITAB software and data analysis fits into various process improvement methodologies as you learn these techniques without all of the confusing jargon learn how to use MINITAB to accurately assess the current performance and capability of a process; demonstrate where improvements have been made; and ensure those improvements remain View Schedule \| Register top Statistical Analysis for Process Improvement using MINITAB – 2.5 days, $1250 including four hours of free coaching and support This course builds upon the prerequisite Introduction to MINITAB and Basic Data Analysis. Statistical analysis of data has become an integral part of almost all quality improvement efforts and practitioners are required to extract valuable information from their processes. This course illustrates statistical tools and techniques that teach how to objectively evaluate processes including ways to quantify and incorporate the uncertainty that accompanies all statistical analyses. This is addressed using formal statistical analysis techniques to estimate critical process characteristics and statistically test theories your team has about those processes. In addition you will: learn how to explore data to discover features and information critical for process improvement develop the foundation required to statistically describe relationships between critical process variables to find root causes of process nonconformity develop the skills which will allow you to understand if a formal statistical analysis will enhance your project objectives learn how to outline the common uses and misuses of statistics in business and industrial applications. learn to ensure your data is truly representative of your process through measurement systems analysis View Schedule \| Register top Design and Analysis of Experiments using MINITAB – 2.5 days, $1250 including four hours free coaching and support This course builds upon the prerequisites Introduction to MINITAB and Basic Data Analysis and Statistical Analysis for Process Improvement using MINITAB. Design and Analysis of Experiments is one of the most powerful sets of statistical tools critical to process optimization. This course will dispense with the simplified examples typically taught in most training courses—that rarely occur in practice—and will address the issues necessary for real world experimentation. Your company will learn how to design and analyze experiments that not only evaluate the integral factors under study but also address the many uncontrollable and unknown external factors that impact all experiments. By honing these skills your team will have the ability to expedite quality improvement efforts by successfully predicting and modeling how processes perform even within complex environments. In addition you will: learn how to study the impact of a large number of experimental factors in a sequential approach preserving the valuable resources and costs required in experimentation learn how to use experimental results to build statistical models that predict process performance under conditions not studied in the experiment learn how to simultaneously optimize multiple process characteristics and competing process objectives. learn how incorporating basic principles of experimentation in the early planning stages greatly simplifies analysis efforts later learn how experimentation can streamline root cause analysis guiding you to the vital few factors impacting your process learn how to plan, conduct, and analyze experiments to optimize the information learned while minimizing time, cost, and resources required to run the experiment View Schedule \| Register top

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