Statistics with Minitab Training Course by SQT

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Note: This course includes Capability Analysis, Control Charts and Hypothesis Testing. There are two alternative versions; Statistics with Minitab (Incl. Gauge R&R and Sampling), which includes Gauge R&R and Acceptance Sampling, and Statistics with Minitab (Incl. Regression Analysis and Stability), which includes Regression Analysis, Stability Studies, and Power of the Test. These alternative brochures are available on request. The tutors are available to explain the difference between these options and to discuss special programmes to meet specific customer requirements.

IT IS NOT POSSIBLE TO UTILISE SAMPLE DATA WITHOUT STATISTICS. Much time and effort is 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 people will choose the appropriate statistical tools for data analysis and understand the outcome of the analysis.

There are several brands of reasonably priced computer statistical software packages available to assist in the application of statistics, and most people with a reasonable background in maths (example, pass leaving certificate level) can be readily trained to use this software so as to utilise data for continual process improvement, and better decision making.

Minitab software will be used throughout the training course. Delegates 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. Where the course is presented In-Company the programme can be modified to include specific statistical applications.

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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

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, but participants should have an understanding of mathematical principles; for example, Leaving Certificate maths.

Participants achieve the following learning outcomes from the programme;

Undertake statistical analysis using Minitab software
Calculate and interpret capability analysis – CP/Cpk and PP/Ppk
Construct and use control charts
Select appropriate statistical tests such as two-sample t, F-test, ANOVA, etc. for comparing data means and variances
Calculate and interpret confidence intervals on population parameters

Albert Plant

With a background of thirty year’s practical experience, Albe...

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Grainne Heneghan

Grainne is a highly experienced Continuous Improvement and Lean...

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In-House Courses
For In-House courses the tutor will contact you in advance to discuss the course programme in more detail in order to tailor it specifically for your organisation.

Course Manual
Delegates will receive a very comprehensive course manual written by the course tutor. The manual incorporates many exercises that the participants will complete during the training course, and these worked examples, along with the relevant graphical material, will serve as a useful reference when the participants return to their workplace.

Minitab will be demonstrated as part of the training so if delegates are in a position to bring along a laptop with Minitab 20, 21 or 22 pre-loaded (free 30 day trial of Minitab 22 available on www.minitab.com) they can utilise this during the training. If delegates don’t have a laptop, they will still benefit greatly from the programme.

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Snapshot

Course Code

CPI010

Duration

3 training days

Public Price

Virtual Training: €995

(includes course documentation)

Delivery Mode

This programme is delivered by Classroom, Virtual Training, or In-Company training

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