Quality Training

Statistics with Minitab Module 1. Basic.

Objectives

This course is designed to give the learner core skills in statistical data analysis with Minitab. It is available as a public or in-company session. For in-company training, we encourage learners to bring their work-related data to maximize their learning experience.

What To Expect
· Discover the Minitab environment.
· Learn how to configure key Minitab features.
· Learn how to import external data into Minitab.
· Learn key fundamentals of data analytics with Minitab – data pre-processing, feature engineering, exploratory data analysis (EDA) etc.
· Learn how to use Minitab to visualize your data – Graph Builder, Bubble plot, Probability Distribution plot, Correlogram etc.
· Learn how to use Minitab to predict your process – normal, t, binomial and Poisson distributions.
· Learn how to use Minitab for parameter estimation and their relevance to process capability analysis – point estimates, confidence intervals, tolerance intervals etc.
· Learn how to make statistical decisions with Minitab – 1-sample t, 2-sample t, paired t tests, F-test, ANOVA etc.
· Learn how to use Minitab for process control and optimization – Run chart, X-bar R, IMR, P and U charts.

Content includes

Day 1: Foundation Statistics with Minitab
1. Minitab Environment

• Projects/Worksheets.
• Menu bar.
• Toolbars.
• Data and output panes.
• Navigator Pane

2. Changing Minitab’s default behaviour

• Configuring Options.
• Customizing your options.
• Managing and creating profiles.

3. Overview of Data Analytics with Minitab

• Importing data from external sources, e.g MS Excel.
• Data pre-processing.
• Feature Engineering.
• Summarising your data numerically.
• Summarising your data graphically using Minitab’s Graph Builder.
• Introduction to Minitab’s Assistant.

4. Understand key statistical concepts and definitions

• Population, sample, types of data etc.
• Measures of dispersion and central tendency and how they relate to process capability – Cp, Pp etc.
• Descriptive and inferential statistics.
• Central Limit Theorem.

5. Some Exploratory Data Analysis (EDA) tools in Minitab

• Histograms, Boxplots, Scatter Plot, Time Series Plots, Matrix Plots, Bubble plot, Individual Value Plot, correlogram etc.
• Use Normal Probability Plot to answer the question “is my data normal?”.
  
  

Day 2: Statistical Decision Making with Minitab
Prerequisite - Introductory Statistics with Minitab

1. Understand concept of probability

• Difference between probability and statistics.
• Simplistic definition of probability.

2. Understand the distribution of your data

• Probability Distributions – normal, t, binomial, Poisson.
• Use probability to make predictions about your process.

3. Know how to estimate key process parameters

• Point estimates.
• Confidence intervals for mean, variance and proportion.
• Use tolerance interval to make a “90/99” confidence statement about your process.

4. Use Tests of Hypotheses to answer the question “Have I made a difference?”

• Z-test, t-test, F-test, Paired t-test.

5. Know how to use Analysis of Variance (ANOVA) to compare multiple sample means.

6. Know how to determine the optimum sample size for decision-making.

Day 3: Process Monitoring & Control with Minitab

Prerequisite - Introductory Statistics with Minitab

1. Understand Central Limit Theorem as justification for control charts.

2. Understand Process Variation.

3. Learn why process variation defines process capability.

4. Construct and interpret control charts for variables

• ImR Chart.
• X-bar/R Chart.
• X-bar/S Chart.

4.Construct and interpret control charts for attributes

• p-Chart.
• np-Chart.
• u-Chart.
• c-Chart.

5. End-of-course Quiz

Who should attend

Personnel from Manufacturing, Quality, R&D, Product Design, Inspection & Test, Process Validation etc.

Upcoming dates:

No training dates available at the moment.