Statistical techniques for data processing and analysis (transactional)
Category: PROBLEM SOLVINGLength: 4 days
Planning:
Training for Services (Transactional)
Objectives:
Understanding data collection, processing, and analysis approach and especially their use in making the right decisions.
Target audience: Personnel from services companies involved in data analysis activities, decision making and continuous improvement activities.
Training duration: 2 days (introductory) / 4 days (full course: introductory + advanced statistics).
Objectives:
Understanding data collection, processing, and analysis approach and especially their use in making the right decisions.
Target audience: Personnel from services companies involved in data analysis activities, decision making and continuous improvement activities.
Training duration: 2 days (introductory) / 4 days (full course: introductory + advanced statistics).
Description:
• Module 1 (2 days) – Introductory, presents general notions about data types, sampling methods as well as the main graphical analysis tools.
• Module 2 (2 days) – Advanced Statistics continue for those interested, data processing and analysis, this time using more complex statistical tools, using hypothesis testing and DOE to obtain the most accurate decisions.
• For a faster and more accurate data processing, one of the two most popular software will be used: SigmaXL or MINITAB.
• The training abounds in exercises, case studies and classroom applications, using intensive the statistical software which is practically learned in parallel with tools application.
• Requires access to PCs with the statistical software installed (for details, contact us)
Presented tools
| Module 1 - Introductory | Module 2 - Advanced Statistics |
| 2 days | 2 days |
| • Basic Statistics • Introduction in SigmaXL / MINITAB • Graphical analysis tools (Dot plot, Histogram, Box Plot, Pareto, Scatter Plots) •Statistical Process Control (SPC) • Control Charts (I-MR, Xbar-R, P chart,) • Capability study (Cpk, Cp, Ppk, Pp) • Introduction to Measurement System Analysis (MSA) • MSA for attributive data |
• Hypothesis testing, introduction • Tools for attributive input data and continuous output data • Tools for non-normal distribution •Tools for attributive input data and discrete output data • Tools for continuous input data and continuous output data •Design of Experiments (DOE) Attendance to this Module is conditioned by the attendance to the previous Module |
Trainer:
Six Sigma Black Belt and Master Black Belt, specialized in the control and optimization of production processes, quality, maintenance, logistics and human resources. Relevant experience in successful application of tools in automotive industry and other industries.
For more information, please contact us.
