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Are you wanting to take your data analytics knowledge to the next level? With Minitab’s Virtual Training courses you will learn to expand your analytics skills by looking at data from real-world problems experienced in a range of industries to explore and describe relationships between variables. Hands-on examples will help you learn how to assess a measurement system, evaluate the stability and capability of a process. Learn how to analyze patterns found in historical data to gain better insights and help you make predictions about the future and build predictive models that improve decision-making. Take that next step by choosing one of our upcoming Virtual Training courses, to assist in up-scaling your data analytics knowledge.
Process Control and Capability - July 14-16
Statistical Quality Analysis
Develop the necessary skills to successfully evaluate and certify manufacturing and engineering measurement systems. Learn the basic fundamentals of statistical process control and how these important quality tools can provide the necessary evidence to improve and control manufacturing processes. Learn how to utilize important capability analysis tools to evaluate your processes relative to internal and customer specifications.
Statistical Tools covered in this course include: Gage R&R; Gage Linearity and Bias; Attribute Agreement Analysis; Control Charts; Probability Plots; Process Capability for Normal and Non-normal Data.
Additional Topics in Statistical Quality Analysis
Continue to build on the fundamental concepts taught in the Manufacturing Statistical Quality Analysis course by learning additional tools that help to improve and control your processes.
Statistical Tools covered in this course include: Gage R&R Expanded; Orthogonal Regression, Tolerance Intervals, Control Charts including EWMA, Short-Run, CUSUM, and Rare Events, Acceptance Sampling.
Predictive Analytics - July 20-22Regression Modeling and ForecastingBuild on your fundamental statistical analysis knowledge by learning to explore and describe relationships between variables with statistical modeling tools. Discover and describe features in data related to the effect and impact of time, and how to forecast future behavior.
Learn how to find and quantify the effect that input variables have on the probability of a critical event occurring. Hands-on examples illuminate how modeling tools help reveal key inputs and sources of variation in your data.
Statistical Tools covered in this course include: Scatter plots; Correlation; Simple Linear Regression; Multiple and Step-wise Regression; Binary Logistic Regression; and Regression with Validation; Time Series Tools including Exponential Smoothing; Trend Analysis; Decomposition.
Machine Learning
Expand your analytics skills by analyzing data from real world problems experienced in many industries to explore and describe relationships between variables. Learn to use supervised machine learning techniques such as CART® to analyze patterns found in historical data to gain better insights, identify potential risks, seek out improvement opportunities and make predictions about the future.
Use unsupervised machine learning tools such as Clustering to detect natural partitions in the data and group observations or variables into homogeneous sets. Reduce the dimensionality of data by transforming the original data into a set of uncorrelated variables.
Statistical Tools covered in this course include: Discriminant Analysis; CART® Classification; CART® Regression; Cluster Analysis; and Principal Components.
Need help deciding which course best fits your needs? Contact us at
training@minitab.com and we'll be happy to assist you!
The Minitab Training Team
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