MINITAB SERIES

minitab

The goal of MINITAB training series is to get the insight you need from your data

 

Minitab provides the tools you need to analyze data and find meaningful solutions to your toughest business problems. Minitab offers a comprehensive set of tools for visualizing, exploring, analyze your date. All classes are delivered by one of our Master Black Trainers. Whether your company has employees new to Minitab or advanced users, our training will cover all you need to know to become a Minitab expert.
Each Minitab course we offer provides the training a specialist will need to understand and use the company data

MINITAB FUNDAMENTALS

In this introductory level Minitab course  you will learn the basics of Minitab and be able

to start using it effectively.

Course level:

fundamentals

Course lenght:

2 days

Who can participate:

Systems analysts, business analysts, six sigma belts, quality professionals,  project managers,

project coordinators, project leaders, team leaders, product managers..

 

 

1 Getting Started with Minitab Statistical Software

 

1.1 Opening a New Minitab Project

1.2 Loading Data into the Project

1.3 Creating a Graph

1.4 Calculating Descriptive Statistics

1.5 Exploring Relationships between Variables

1.6 Brushing Data

1.7 Navigating with the Project Manager

1.8 Creating a Report

1.9 Find Out More

Quiz

 

2 Analyzing and Comparing Variables with Graphs

 

2.1 Graphing the Distribution of One Variable

2.2 Comparing Distributions of Multiple Variables

2.3 Graphs of Quantitative Y Versus Categorical X Variables

2.4 Graphing in Three Dimensions

2.5 Other Graphs in Minitab

2.6 Find Out More

Quiz

3 Exploring the Minitab Environment

 

3.1 Data Types in Minitab

3.2 Working with Excel and Minitab

3.3 Minitab Session Commands

3.4 Constants, Columns, and Matrices

3.5 File Types in Minitab

3.6 Menus in Minitab

3.7 Toolbars in Minitab

3.8 Customizing Minitab

Quiz

 

4 Selecting and Using Distribution Models in Minitab

 

4.1 Graphing Probability Mass Functions and Density Functions

4.2 Probability and Quantile Calculations

4.3 Generating Random Numbers

4.4 Selecting a Distribution Model

4.5 Selecting a Normalizing Transformation

4.6 Meet the Distributions

4.7 A Word of Caution

4.8 Find Out More

RECAP and EXAM

MINITAB ADVANCED

Benefits:

At the end of this training the participants will be able to gain familiarity with Minitab and  increased  effectiveness and efficiency of data analysis and improved  knowledge of statistics.

Course level:

advanced

Course lenght:

4 days

Who can participate:

Systems analysts, business analysts, six sigma belts, quality professionals,  project managers, project coordinators, project leaders, team leaders, product managers.

1.1 Introduction

1.1.1 Learning Objectives

1.2 Types of Data

1.2.1 Basic Concepts

1.2.2 Data Types

1.2.3 Quiz: Types of Data

1.3 Using Graphs to Analyze Data

1.3.1 Basic Concepts

1.3.2 Bar Charts and Pareto Charts

1.3.3 Pie Charts

1.3.4 Histograms

1.3.5 Dotplots

1.3.6 Individual Value Plots

1.3.7 Boxplots

1.3.8 Time Series Plots

1.3.9 Quiz: Using Graphs to Analyze Data

1.3.10 Minitab Tools: Bar Chart

1.3.11 Minitab Tools: Pie Chart

1.3.12 Minitab Tools: Histogram

1.3.13 Minitab Tools: Dotplot

1.3.14 Minitab Tools: Individual Value Plot

1.3.15 Minitab Tools: Boxplot

1.3.16 Minitab Tools: Times Series Plot

1.3.17 Exercise: Graphical Analysis

1.4 Using Statistics to Analyze Data

1.4.1 Basic Concepts

1.4.2 Mean and Median

1.4.3 Range, Variance, and Standard Deviation

1.4.4 Quiz: Using Statistics to Analyze Data

1.4.5 Minitab Tools: Display Descriptive Statistics

1.4.6 Exercise: Descriptive Statistics

1.5 Summary

1.5.1 Objectives Review

Chapter 2: Statistical Inference

2.1 Introduction

2.1.1 Learning Objectives

2.2 Fundamentals of Statistical Inference

2.2.1 Basic Concepts

2.2.2 Random Samples

2.2.3 Quiz: Fundamentals of Statistical Inference

2.2.4 Minitab Tools: Random Sampling

2.3 Sampling Distributions

2.3.1 Basic Concepts

2.3.2 Sampling Distribution of the Mean

2.3.3 Quiz: Sampling Distributions

2.4 Normal Distribution

2.4.1 Basic Concepts

2.4.2 Probabilities Associated with a Normal Distribution

2.4.3 Probabilities Associated with the Sample Mean

2.4.4 Quiz: Normal Distribution

2.4.5 Minitab Tools: Cumulative Probabilities with a Normal Distribution

2.4.6 Exercise: Probabilities and Normal Distributions

2.5 Summary

2.5.1 Objectives Review

Chapter 3: Hypothesis Tests and Confidence Intervals

3.1 Introduction

3.1.1 Learning Objectives

3.2 Tests and Confidence Intervals

3.2.1 Confidence Intervals

3.2.2 Hypothesis Testing

3.2.3 Using Hypothesis Testing to Make Decisions

3.2.4 Type I and Type II Errors and Power

3.2.5 Quiz: Tests and Confidence Intervals

3.3 1-Sample t-Test

3.3.1 Basic Concepts

3.3.2 Individual Value Plots

3.3.3 1-Sample t-Test Results

3.3.4 Assumptions

3.3.5 Quiz: 1-Sample t-Test

3.3.6 Minitab Tools: 1-Sample t-Test

3.3.7 Exercise: 1-Sample t-Test

3.4 2 Variances Test

3.4.1 Basic Concepts

3.4.2 Boxplots

3.4.3 2 Variances Test Results 3.4.4 Assumptions

3.4.5 Quiz: 2 Variances Test

3.4.6 Minitab Tools: 2 Variances Test

3.4.7 Exercise: 2 Variances Test

3.5 2-Sample t-Test

3.5.1 Basic Concepts

3.5.2 Individual Value Plot

3.5.3 2-Sample t-Test Results

3.5.4 Assumptions

3.5.5 Quiz: 2-Sample t-Test

3.5.6 Minitab Tools: 2-Sample t-Test

3.5.7 Exercise: 2-Sample t-Test

3.6 Paired t-Test

3.6.1 Basic Concepts

3.6.2 Individual Value Plots

3.6.3 Paired t-Test Results

3.6.4 Assumptions

3.6.5 Quiz: Paired t-Test

3.6.6 Minitab Tools: Paired t-Test

3.6.7 Exercise: Paired t-Test

3.7 1 Proportion Test

3.7.1 Basic Concepts

3.7.2 1 Proportion Test Results

3.7.3 Assumptions

3.7.4 Quiz: 1 Proportion Test

3.7.5 Minitab Tools: 1 Proportion Test

3.7.6 Exercise: 1 Proportion Test

3.8 2 Proportions Test

3.8.1 Basic Concepts

3.8.2 2 Proportions Test Results

3.8.3 Assumptions

3.8.4 Quiz: 2 Proportions Test

3.8.5 Minitab Tools: 2 Proportions Test

3.8.6 Exercise: 2 Proportions Test

3.9 Chi-Square Test

3.9.1 Basic Concepts

3.9.2 Chi-Square Test Results

3.9.3 Assumptions

3.9.4 Quiz: Chi-Square Test

3.9.5 Minitab Tools: Chi-Square Test

3.9.6 Exercise: Chi-Square Test

3.10 Summary

3.10.1 Objectives Review

Chapter 4: Control Charts

4.1 Introduction

4.1.1 Learning Objectives

4.2 Statistical Process Control

4.2.1 Basic Concepts

4.2.2 Patterns in Control Charts

4.2.3 Quiz: Statistical Process Control

4.3 Control Charts for Variables Data in Subgroups

4.3.1 Basic Concepts

4.3.2 R Charts

4.3.3 S Charts

4.3.4 Xbar Charts

4.3.5 Quiz: Control Charts for Variables Data in Subgroups

4.3.6 Minitab Tools: Xbar-R Chart

4.3.7 Exercise: Xbar-R Chart

4.4 Control Charts for Individual Observations

4.4.1 Basic Concepts

4.4.2 Moving Range Charts

4.4.3 Individuals Charts

4.4.4 Quiz: Control Charts for Individual Observations

4.4.5 Minitab Tools: I-MR Chart

4.4.6 Exercise: I-MR Chart

4.5 Control Charts for Attribute Data

4.5.1 Basic Concepts

4.5.2 NP and P Charts

4.5.3 C and U Charts

4.5.4 Quiz: Control Charts for Attributes Data

4.5.5 Minitab Tools: P Chart

4.5.6 Exercise: P Chart

4.6 Summary

4.6.1 Objectives Review

Chapter 5: Process Capability

5.1 Introduction

5.1.1 Learning Objectives

5.2 Process Capability for Normal Data

5.2.1 Basic Concepts

5.2.2 Assumptions

5.2.3 Testing for Normality

5.2.4 Quiz: Process Capability for Normal Data

5.2.5 Minitab Tools: Normality Test

5.2.6 Exercise: Assumptions for Process Capability

5.3 Capability Indices

5.3.1 Potential Capability: Cp and Cpk

5.3.2 Process Performance: Pp and Ppk

5.3.3 Sigma Level

5.3.4 Quiz: Capability Indices

5.3.5 Minitab Tools: Cp and Pp

5.3.6 Minitab Tools: Sigma Level

5.3.7 Exercise: Process Capability for Normal Data

5.4 Process Capability for Nonnormal Data

5.4.1 Transformations and Alternate Distributions

5.4.2 Box-Cox Transformation

5.4.3 Johnson Transformation

5.4.4 Alternate Distributions

5.4.5 Quiz: Process Capability for Nonormal Data

5.4.6 Minitab Tools: Box-Cox Transformation

5.4.7 Minitab Tools: Johnson Transformation

5.4.8 Minitab Tools: Capability Analysis with Johnson Transformation

5.4.9 Minitab Tools: Alternate Distributions

5.4.10 Minitab Tools: Capability Analysis with Alternate Distributions

5.4.11 Exercise: Process Capability with Data Tranformations

5.4.12 Exercise: Process Capability with Alternate Distributions

5.5 Summary

5.5.1 Objectives Review

Chapter 6: Analysis of Variance (ANOVA)

6.1 Introduction

6.1.1 Learning Objectives

6.2 Fundamentals of ANOVA

6.2.1 Basic Concepts

6.2.2 Graphs and Summary Statistics

6.2.3 Quiz: Fundamentals of ANOVA

6.3 One-Way ANOVA

6.3.1 Hypothesis Tests

6.3.2 F-Statistics and P-Values

6.3.3 Multiple Comparisons

6.3.4 Assumptions and Residual Plots

6.3.5 Quiz: One-Way ANOVA

6.3.6 Minitab Tools: One-Way ANOVA

6.3.7 Exercise: One-Way ANOVA

6.4 Two-Way ANOVA

6.4.1 Basic Concepts

6.4.2 Graphs

6.4.3 Hypothesis Tests

6.4.4 F-Statistics and P-Values

6.4.5 Assumptions and Residual Plots

6.4.6 Quiz: Two-Way ANOVA

6.4.7 Minitab Tools: Two-Way ANOVA

6.4.8 Exercise: Two-Way ANOVA

6.5 Summary

6.5.1 Summary of ANOVA

Chapter 7: Correlation and Regression

7.1 Introduction

7.1.1 Learning Objectives

7.2 Relationship Between Two Quantitative Variables

7.2.1 Basic Concepts

7.2.2 Scatterplot

7.2.3 Correlation

7.2.4 Quiz: Relationship Between Two Quantitative Variables

7.2.5 Minitab Tools: Scatterplot

7.2.6 Minitab Tools: Correlation

7.2.7 Exercise: Scatterplots and Correlation

7.3 Simple Regression

7.3.1 Basic Concepts

7.3.2 Regression

7.3.3 Hypothesis Tests and R2

7.3.4 Assumptions and Residual Plots

7.3.5 Quiz: Simple Regression

7.3.6 Minitab Tools: Simple Regression

7.3.7 Exercise: Simple Regression

7.4 Summary

7.4.1 Objectives Review

Chapter 8: Measurement Systems Analysis

8.1 Introduction

8.1.1 Learning Objectives

8.2 Fundamentals of Measurement Systems Analysis

8.2.1 Basic Concepts

8.2.2 Accuracy

8.2.3 Precision

8.2.4 Comparing Accuracy and Precision

8.2.5 Quiz: Fundamentals of Measurement Systems Analysis

8.3 Repeatability and Reproducibility

8.3.1 Basic Concepts

8.3.2 Gage R&R Studies

8.3.3 Quiz: Repeatability and Reproducibility

8.4 Graphical Analysis of a Gage R&R Study

8.4.1 Basic Concepts

8.4.2 Components of Variation

8.4.3 Xbar and R Charts

8.4.4 Interaction between Operator and Part

8.4.5 Comparative Plots

8.4.6 Gage Run Charts

8.4.7 Quiz: Graphical Analysis of a Gage R&R Study

8.4.8 Minitab Tools: Crossed Gage R&R Study

8.4.9 Minitab Tools: Gage Run Chart

8.4.10 Exercise: Graphical Analysis of a Gage R&R Study

8.5 Variation

8.5.1 Standard Deviation and Study Variation

8.5.2 Tolerance

8.5.3 Process Variation

8.5.4 Quiz: Variation

8.5.5 Exercise: Numerical Analysis of a Gage R&R Study

8.6 ANOVA with a Gage R&R Study

8.6.1 Variance Components

8.6.2 Analysis of Variance Tables

8.6.3 Quiz: ANOVA with a Gage R&R Study

8.6.4 Exercise: ANOVA Output for a Gage R&R Study

8.7 Gage Linearity and Bias Study

8.7.1 Basic Concepts

8.7.2 Gage Linearity

8.7.3 Gage Bias

8.7.4 Quiz: Gage Linearity and Bias Study

8.7.5 Minitab Tools: Gage Linearity and Bias Study

8.7.6 Exercise: Gage Linearity and Bias Study

8.8 Attribute Agreement Analysis

8.8.1 Basic Concepts

8.8.2 Binary Data

8.8.3 Nominal Data

8.8.4 Ordinal Data

8.8.5 Quiz: Attribute Agreement Analysis

8.8.6 Minitab Tools: Attribute Agreement Analysis with Binary Data

8.8.7 Minitab Tools: Attribute Agreement Analysis with Nominal Data

8.8.8 Minitab Tools: Attribute Agreement Analysis with Ordinal Data

8.8.9 Exercise: Attribute Agreement Analysis

8.9 Summary

8.9.1 Objectives Review

Chapter 9: Design of Experiments

9.1 Introduction

9.1.1 Learning Objectives

9.2 Factorial Designs

9.2.1 Basic Concepts

9.2.2 Creating Full Factorial Designs

9.2.3 Analyzing Full Factorial Designs

9.2.4 Quiz: Factorial Designs

9.2.5 Minitab Tools: Create a Full Factorial Design

9.2.6 Minitab Tools: Analyze a Full Factorial Design

9.2.7 Exercise: Create a Full Factorial Design

9.2.8 Exercise: Analyze a Full Factorial Design

9.3 Blocking and Incorporating Center Points

9.3.1 Blocking

9.3.2 Center Points

9.3.3 Analyzing Designs with Blocks and Center Points

9.3.4 Quiz: Blocking and Incorporating Center Points

9.3.5 Minitab Tools: Create a Factorial Design with Blocks and Center Points

9.3.6 Minitab Tools: Analyze a Factorial Design with Blocks and Center Points

9.3.7 Exercise: Create a Factorial Design with Blocks and Center Points

9.3.8 Exercise: Analyze a Factorial Design with Blocks and Center Points

9.4 Fractional Factorial Designs

9.4.1 Basic Concepts

9.4.2 Creating Fractional Factorial Designs

9.4.3 Analyzing Fractional Factorial Designs

9.4.4 Quiz: Fractional Factorial Designs

9.4.5 Minitab Tools: Create a Fractional Factorial Design

9.4.6 Minitab Tools: Analyze a Fractional Factorial Design

9.5 Response Optimization

9.5.1 Response Optimization

9.5.2 Quiz: Response Optimization

9.5.3 Minitab Tools: Response Optimization

9.5.4 Exercise: Response Optimization

9.6 Summary

9.6.1 Objectives Review

 

RECAP and EXAM

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