Length of training: 2 Days Day 1: Introduction to Minitab Decrease the time required for statistical analysis by quickly learning to navigate Minitab’s user-friendly and customizable environment. Learn how to import/export data and output between Minitab and various software and database systems. Enhance your ability to create, manipulate, and restructure data. Develop sound statistical approaches to data analysis by learning how to create and interpret a wide variety of graphs and numerical measures useful for quality improvement initiatives. This course focuses on the utilization of these tools as they pertain to applications commonly found in business, transactional, and service industries. Topics covered include: Pareto Charts, Time Series plots, Individual value plots, Bar charts, Histograms, Boxplots, Dotplots, Scatterplots, Tables, Measures of Location and Variation, ODBC. Target participants: Professionals who are working in financial services, healthcare and other areas that use metrics such as time, defect rates, and revenue data. The course materials include more examples of analyzing categorical (count) data than continuous (measurement) data. Day 2: Basic Statistics Augment your graphical analysis skills using Minitab’s powerful statistical tools. Develop the foundation for important statistical concepts such as hypothesis testing and confidence intervals. By analyzing a variety of real world data sets, learn how to match the appropriate statistical tool to your own applications and how to correctly interpret statistical output to quickly reveal problems with a process or to show evidence of an improvement. Learn how to explore critical features in your processes through statistical modeling tools that help to uncover and describe relationships between variables. The course emphasis is on making good business decisions through the use of statistical tools commonly used in business, transactional, and service processes. Tools Covered Include: t-Tests, Proportion Tests, Tests for Equal Variance, Power and Sample Size, Tables and Chi-Square Analysis, Correlation, Simple Linear Regression, ANOVA. Target participants: Professionals who are working in financial services, healthcare and other areas that use metrics such as time, defect rates, and revenue data. The course materials include more examples of analyzing categorical (count) data than continuous (measurement) data. |
