Minitab für statistische Datenanalyse Training Course

Primary tabs

Course Code

mtstatda

Duration Duration

14 hours (usually 2 days including breaks)

Requirements Requirements

Should be familiar with the basics of excel and statistics

Overview Overview

The course is aimed at anyone interested in statistical analysis. It provides familiarity with Minitab and will increase the effectiveness and efficiency of your data analysis and improve your knowledge of statistics.

Course Outline Course Outline

Chapter 1: Descriptive Statistics and Graphical Analysis

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


Public Classroom Public Classroom
Participants from multiple organisations. Topics usually cannot be customised
From 2350EUR
(80)
Private Classroom Private Classroom
Participants are from one organisation only. No external participants are allowed. Usually customised to a specific group, course topics are agreed between the client and the trainer.
Private Remote Private Remote
The instructor and the participants are in two different physical locations and communicate via the Internet
From 1850EUR
Request quote

The more delegates, the greater the savings per delegate. Table reflects price per delegate and is used for illustration purposes only, actual prices may differ.

Number of Delegates Public Classroom Private Remote
1 2350EUR 1850EUR
2 1500EUR 1225EUR
3 1217EUR 1017EUR
4 1075EUR 913EUR
Cannot find a suitable date? Choose Your Course Date >>
Too expensive? Suggest your price

Related Categories


Upcoming Courses

VenueCourse DateCourse Price [Remote / Classroom]
ZürichMon, 2017-03-13 09:301850EUR / 2350EUR
BernMon, 2017-03-27 09:301850EUR / 2350EUR
BaselThu, 2017-04-06 09:301850EUR / 2350EUR

Course Discounts

Course Discounts Newsletter

We respect the privacy of your email address. We will not pass on or sell your address to others.
You can always change your preferences or unsubscribe completely.

Some of our clients