training Introduction

Minitab is a powerful statistical tool for Six Sigma implementation. Minitab is one of the known analytical tool for Six Sigma practitioners worldwide. From last three decades, thousands of re-known organisations in nearly ninety countries have turned to Minitab tools that will help to enhance quality initiatives yielding bottom-line benefits.

In this Minitab training with Six Sigma, delegates will gain practical experience to become confident users of the tool. After the completion of one the course, delegates will get expertise in using Minitab to solve complex calculations for projects such as Six Sigma and Lean Six Sigma.

  • Collect the correct data and prepare it for analysis

  • Design effective experiments to optimise a process

  • Analyse your data to gain insight into your business

  • Apply advanced statistical methods for quality improvement

  • Interpret results to make data-driven decisions

  • Create clear presentations to summarise your findings

trainingCourse Details

Minitab is a one-day training course that will train delegates to use Minitab for business improvement projects. Our team offers comprehensive Minitab training, so that delegates will be able to use its functionality. Delegates will provide practical experience with Minitab to make sure that delegates will get confident with this tool.

The introduction to Minitab is aimed at providing enough knowledge to the delegates to help them start and use the essential features of Minitab. Of course, delegates will also learn about Minitab functionalities and its concepts as one will proceed further in the course.New Features in Minitab 17

Descriptive Statistics and Graphical Analysis

  • Types of Data
    • Basic Concepts
    • Data Types
    • Types of Data
  • Using Graphs to Analyse Data
    • Basic Concepts
    • Bar Charts and Pareto Charts
    • Pie Charts
    • Histograms
    • Dot plots
    • Individual Value Plots
    • Boxplots
    • Time Series Plots
    • Using Graphs to Analyse Data
    • Bar Chart
    • Pie Chart
    • Histogram
    • Dot plot
    • Individual Value Plot
    • Boxplot
    • Times Series Plot
    • Graphical Analysis
  • Using Statistics to Analyse Data
    • Basic Concepts
    • Mean and Median
    • Range, Variance, and Standard Deviation
    • Using Statistics to Analyse Data
    • Display Descriptive Statistics

Statistical Inference

  • Introduction
    • Fundamentals of Statistical Inference
    • Basic Concepts
    • Random Samples
    • Fundamentals of Statistical Inference
    • Random Sampling
  • Sampling Distributions
    • Basic Concepts
    • Sampling Distribution of the Mean
    • Sampling Distributions
  • Normal Distribution
    • Basic Concepts
    • Probabilities Associated with a Normal Distribution
    • Probabilities Associated with the Sample Mean
    • Normal Distribution
    • Cumulative Probabilities with a Normal Distribution
    • Probabilities and Normal Distributions

Hypothesis Tests and Confidence Intervals

  • Tests and Confidence Intervals
    • Confidence Intervals
    • Hypothesis Testing
    • Using Hypothesis Testing to Make Decisions
    • Type I/Type II Errors and Power
  • 1-Sample t-Test
    • Basic Concepts
    • Individual Value Plots
    • 1-Sample t-Test
  • Variances Test
    • Basic Concepts
    • Boxplots
    • 2 Variances Test
    • Assumptions
  • 2-Sample t-Test
    • Basic Concepts
    • Individual Value Plot
    • 2-Sample t-Test Results
    • 2-Sample t-Test
  • Paired t-Test
    • Basic Concepts
    • Individual Value Plots
    • Paired t-Test Results
    • Assumptions
    • Paired t-Test
  • Proportion Test
    • Basic Concepts
    • 1 Proportion Test
    • Assumptions
  • Proportions Test
    • Basic Concepts
    • 2 Proportions Test Results
    • Assumptions
    • 2 Proportions Test
  • Chi-Square Test
    • Basic Concepts
    • Chi-Square Test Results
    • Assumptions
    • Chi-Square Test

Control Charts

  • Statistical Process Control
    • Basic Concepts
    • Patterns in Control Charts
    • Statistical Process Control
  • Control Charts for Variables Data in Subgroups
    • Basic Concepts
    • R Charts
    • S Charts
    • X-bar Charts
    • Control Charts for Variables Data in Subgroups
  • Control Charts for Individual Observations
    • Basic Concepts
    • Moving Range Charts
    • Individuals Charts
    • Control Charts for Individual Observations
    • I-MR Chart
  • Control Charts for Attribute Data
    • Basic Concepts
    • NP and P Charts
    • C and U Charts
    • Control Charts for Attributes Data
    • P Chart

Process Capability

  • Process Capability for Normal Data
    • Basic Concepts
    • Assumptions
    • Testing for Normality
    • Process Capability for Normal Data
    • Normality Test
    • Assumptions for Process Capability
  • Capability Indices
    • Potential Capability: Cp and Cpk
    • Process Performance: Pp and Ppk
    • Sigma Level
    • Capability Indices
    • Cp and Pp
    • Sigma Level
    • Process Capability for Normal Data
  • Process Capability for Non-normal Data
    • Transformations and Alternate Distributions
    • Box-Cox Transformation
    • Johnson Transformation
    • Alternate Distributions
    • Process Capability for Normal Data
    • Capability Analysis with Johnson Transformation
    • Alternate Distributions
    • Capability Analysis with Alternate Distributions
    • Process Capability with Data Transformations
    • Process Capability with Alternate Distributions

Analysis of Variance (ANOVA)

  • Fundamentals of ANOVA
    • Basic Concepts
    • Graphs and Summary Statistics
    • Fundamentals of ANOVA
  • One-Way ANOVA
    • Hypothesis Tests
    • F-Statistics and P-Values
    • Multiple Comparisons
    • Assumptions and Residual Plots
    • One-Way ANOVA
  • Two-Way ANOVA
    • Basic Concepts
    • Graphs
    • Hypothesis Tests
    • F-Statistics and P-Values
    • Assumptions and Residual Plots
    • Two-Way ANOVA

Correlation and Regression

  • Relationship Between Two Quantitative Variables
    • Basic Concepts
    • Scatterplot
    • Correlation
    • Relationship Between Two Quantitative Variables
  • Simple Regression
    • Basic Concepts
    • Regression
    • Hypothesis Tests and R2
    • Assumptions and Residual Plots
    • Simple Regression

Measurement Systems Analysis

  • Fundamentals of Measurement Systems Analysis
  • Basic Concepts
  • Accuracy
  • Precision
  • Comparing Accuracy and Precision
  • Fundamentals of Measurement Systems Analysis
  • Repeatability and Reproducibility
  • Concepts
  • Study of Gage R&R Study and it graphical Analysis
  • Basic Concepts
  • Components of Variation
  • X-bar and R Charts
  • Interaction between Operator and Part
  • Comparative Plots
  • Gage Run Charts
  • Study of Gage R&R Study and it graphical Analysis
  • Crossed Gage R&R Study
  • Gage Run Chart
  • Variation
  • Standard Deviation and Study Variation
  • Tolerance
  • Process Variation 
  • Variation
  • Study the Numerical Analysis of a Gage R&R
  • ANOVA with a Gage R&R Study
    • Variance Components
    • Analysis of Variance Tables
    • ANOVA with a Gage R&R Study
  • Gage Linearity and Bias Study
    • Basic Concepts
    • Gage Linearity
    • Gage Bias
    • Gage Linearity and Bias Study
    • Gage Linearity and Bias Study
  • Attribute Agreement Analysis
    • Basic Concepts
    • Binary Data
    • Nominal Data
    • Ordinal Data
    • Attribute Agreement Analysis with Binary Data
    • Attribute Agreement Analysis with Nominal Data
    • Attribute Agreement Analysis with Ordinal Data
    • Attribute Agreement Analysis

Design of Experiments

  • Factorial Designs
  • Basic Concepts
  • Creating Full Factorial Designs
  • Analysing Full Factorial Designs
  • Factorial Designs
  • Create a Full Factorial Design
  • Analyse a Full Factorial Design
  • Create a Full Factorial Design
  • Analyse a Full Factorial Design
  • Blocking and Incorporating Center Points
    • Blocking
    • Center Points
    • AnalysingDesigns with Blocks and Center Points
    • Blocking and Incorporating Center Points
    • Build a Factorial Design using Blocks and Center Points
  • Analyse a Factorial Design with Blocks and Center Points
  • Fractional Factorial Designs
    • Basic Concepts
    • Creating Fractional Factorial Designs
    • Analysing Fractional Factorial Designs
    • Fractional Factorial Designs
    • Create a Fractional Factorial Design
    • Analyse a Fractional Factorial Design
  • Response Optimisation
    • Overview of Response Optimisation

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