Technical Training

Statistics with Minitab

Objectives

It is not possible to utilise sample data without statistics. Much time and effort are devoted to the collection of data in industry, for example, quality control measurements, data collected for validation of manufacturing processes, incoming and outgoing inspection data,data produced in the development of products in R&D, etc. It is not possible to get value from this data without using statistics. Many people who use statistical tools such as Statistical Process Control, Design of Experiments, sampling standards, gauge R&R, and other applications don’t understand the underlying statistics. This course is intended to provide that essential understanding so that participants will choose the appropriate statistical tools for data analysis and understand the outcome of the analysis.

Minitab software will be used throughout the training course and participants will be trained to use both the main menus and the Assistant in Minitab to undertake the analysis that will be met in the Programme set out below. .

Content includes

Day 1:

• Outline of the applications of statistics such as Statistical Process Control, Design of Experiments, Sampling, and the relationship with the underlying statistics.
• Explanation of how statistics are used to obtain valuable information on processes from sample data
• Description of statistical terms including population, parameter, random sample, expected value
• Types of data – continuous (variables) and discrete (attributes) data
• Construction of a histogram and explanation of the meaning of frequency distributions, cumulative frequency distributions, measures of dispersion and central tendency
• Graphical methods – box-and-whisker plots, scatter plots
• The normal distribution – testing for normality – Anderson Darling and Ryan Joiner tests
• Normal and Weibull probability plots
• Dealing with non-normal data – Box-Cox and Johnson transformation, distribution fitting using Weibull, Smallest Extreme Value, Largest Extreme Value, etc.
• Capability analysis – CPk/Ppk and percent out of specification

Day 2:

• Central limit theorem and sampling distribution of the mean
• Control charts for variables
• Explanation of the role of control charts in capability analysis and explanation of why there is a difference between Cpk and Ppk
• Calculation of the confidence interval for the mean in variables and attribute data
• Commencement of Hypothesis testing – tests for means, variances and proportions – Z-test, t-test, 2-sample t-test, Paired test, F-test, meaning of significance level

Day 3:

• Hypothesis testing continued from day 2
• Meaning of the P-value in hypothesis testing and how the rules for assessing P are derived
• Analysis of variance (ANOVA) – analysis of a designed experiment illustrating the ANOVA – using Tukey’s pairwise multiple-sample comparison to compare population means

Who should attend

Engineers, technicians, laboratory, R&D, and scientific staff

All personnel involved in quality control

All personnel who have a role in analyzing and understanding manufacturing and business data

Inspection staff

Personnel who use process improvement techniques in their work

People planning to attend Six Sigma Black Belt training courses

People studying for MBA’s and other examinations involving statistics.

A prior knowledge of statistics is not required for this course, but participants should have an understanding of mathematical principles; for example, Leaving Certificate maths.

Upcoming dates:

No training dates available at the moment.