« Continual Process Improvement

Statistics with Minitab


Date Venue Days Price
TBCDublin3€ 995EnquireBook

Statistics with Minitab

Three Day Training Course


 

Background

 

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 most value from this data without using statistics.  Many people are using statistical tools such as Statistical Process Control, Design of Experiments, sampling standards, gauge R&R, and other applications without having an understanding of the underlying statistics.  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.



Learning Outcomes

 

On successful completion of this training course, delegates should be able to:

 

  • Undertake statistical analysis using Minitab software
  • 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
  • Determine sample sizes for statistical tests 
  • Model data using regression analysis

 

 

Who Should Attend

 

  • Engineers, technicians, laboratory, R&D, and scientific staff
  • All personnel involved in quality control
  • All personnel who have a role in analysing 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.

 

 

Course Programme

 

Day 1

  • Description of statistical terms including population, parameter, random sample, expected value
  • Types of data – continuous (variables) and discrete (attributes) data
  • Measurement scales – nominal, ordinal, interval, and ratio measurement scales
  • Methods for collecting data – check sheets, coding data, automatic gauging
  • Basic probability concepts – independence, mutually exclusive, multiplication rules, complementary probability, joint occurrence of events
  • Construction of a histogram and explanation of the meaning of frequency distributions, cumulative frequency distributions, measures of dispersion and central tendency
  • The normal distribution
  • Dealing with non-normal data – Box-Cox and Johnson transformation, distribution fitting
  • Central limit theorem and sampling distribution of the mean
  • Interpreting the efficiency and bias of estimators - standard error, confidence intervals, and tolerance intervals

 

Day 2

  • Other continuous distributions - the uniform, exponential, lognormal, Weibull, Chi-square, Student’s t and F distributions
  • Normal and Weibull probability plots
  • Discrete distributions – binomial, Poisson, hypergeometric distributions
  • Graphical methods – stem and leaf plots, box-and-whisker plots, run charts, scatter diagrams
  • Hypothesis testing – tests for means, variances and proportions – meaning of significance level, Type I and Type II error – difference between statistical and practical significance
  • Sample sizes for hypothesis testing – the effect on Power
  • Paired comparison tests
  • Goodness-of-fit tests

 

Day 3

  • Analysis of variance (ANOVA)
  • Contingency tables
  • Simple and multiple linear regression.  Calculation of the regression equation. Hypothesis testing of the regression statistics.  Using the regression model for estimation and prediction.  Analysing the uncertainty in the estimate
  • Simple linear correlation – calculating the correlation coefficient and its confidence limit.  Hypothesis tests for the correlation coefficient.
  • Non-parametric tests including Mann-Whitney and Kruskall-Wallis

 

 

Software

Minitab will be demonstrated as part of the training so if delegates are in a position to bring along a laptop with Minitab 16 or Minitab 17 pre-loaded (free 30 day trial of Minitab 17 available on www.minitab.co.uk) they can utilise this during the training.  If delegates don’t have a laptop, they will still benefit greatly from the programme.


 

Course Tutor                          Albert Plant

 

Testimonials                          Click Here

 

Course Times                        9.00am - 5.00pm

 

Public Course Cost              €995 (includes course documentation, lunch and refreshments)

 

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. 

 

Rev 11