Data Analysis With Minitab
Learn how to use and apply Minitab data analysis!
Minitab is recognised as a leading platform in the field of data analysis.
Use Minitab to visualise, analyse and harness the power of your data to solve your toughest business problems.
Despite it’s enormous power, Minitab has a friendly user interface that makes it easy for complete beginners to get started and then move on to more sophisticated techniques.
We have been using Minitab for over 20 years in countless data analysis scenarios with more than 100 organisations. It remains our favourite route to understanding data, converting this to valuable information, and making the right business decisions as a result.
The training on offer here gives you options from complete beginner to analysis of complex experimental designs.
What will you learn?
Our training consists of a number of stand alone modules. Whilst you can pick and choose the ones of interest, all of the modules do build on one another.
If you haven’t used Minitab in earnest before we highly recommend you start with our “Introduction to Data Analysis” course.
The training is delivered as a series of video conferencing sessions with email support where required.
You will be part of a small select cohort of participants.
Each of our 5 modules is delivered as a 2 day session. The modules are detailed below.
A full set of colour printed notes will be provided for each module.
This training will give you a practitioner level capability in the use of Minitab. You will leave the course with sufficient understanding to apply the techniques in practice and demonstrate effective data analysis and decision making.
A Training Completion Certificate is issued on completion of these modules.
This is a course for people who want to make a significant positive impact on their organisation and enjoy the satisfaction and recognition for their contribution.
The Minitab Training Modules/Training Syllabus
- Getting started with Minitab
- Graphical techniques – how to collect, analyse, interpret, display and present data
- Summarising data
- Understanding process behaviour
- Making comparisons between processes
- Finding relationships between process variables
- How to find the most important variables when many exist
- How to trend performance
- The Normal Distribution and why it is so important in processes
- Confidence Intervals – knowing how representative your data is
- Process Sigma Measure
- Process Capability analysis – performance vs customer expectations
- Process behaviour – capability versus control
- Natural and abnormal process performance
- Events and designs
- When to intervene in a process and when to leave it alone!
- Controlling inputs and outputs
- I, mR, X-bar, R, S, p, np, c, u, and Cusum – the control toolkit
- Showing the process history
- Performance against expectation
- Capability in more detail – Cp, Cpk, Pp,Ppk,and PPM
- Measurement systems analysis
- Making good decisions
- Comparing process performance against expectations and standards.
- Identifying subtle but important differences in process performance.
- Defining a hypothesis about your data and then challenging that hypothesis to see if it holds good!
- Sampling distributions
- Confidence levels, Alpha and Beta risks
- Stating your conclusions
- The test menu, 1-sample Z, 1-sample t, 2-sample t, F-test, Chi-Square Tests, Contingency Tables, Proportions Tests – covers what these tests mean and how they can be used in a host of business decision scenarios.
- The cost of variation.
- The multiple sources of variation.
- How to analyse variation sources and identify potential fixes.
- Handling factors which interact to produce process variation.
- Determining factors that are significant / not significant
- The toolkit of ANOVA in depth – one-way, two way, balanced, fixed, random, nested, crossed.
- Analysis diagnostics
- Efficient comparison techniques
- Interpretation of results
- Last but by no means least – we look at variation in measurement systems
- The history of experimentation and how it applies to us today
- How to find process solutions when a host of variables are at play
- The drawbacks of looking at one factor at a time
- How to design a trial / experiment
- Main Effects and Interaction Effects
- Full and partial factorial designs
- Zooming in on the main factors that define your process performance
- Response Surface Analysis
Who should participate?
- People who are interested in their own personal development and who would like to learn how best to gather, analyse, display, interpret and make decisions with data.
- Anyone looking for career development via this certificated programme.
- People who want to upskill their problem solving capabilities and demonstrate what they can achieve within their organisation.
- Anyone looking for their first formal training in data based decision making.
- Academic qualifications are not required, but reasonable numeracy and familiarity with using Excel will be useful.