TRAINING MINITAB

 

Rolul sesiunii de 3 zile de training MINITAB este de a va familiariza cu colectarea, vizualizarea  si analiza datelor de business

Minitab aduce instrumentele necesare pentru analiza datelor si gasirea unor solutii la cele mai dificile probleme de business. Minitab ofera un pachet complet de instrumente pentru vizualizarea, explorarea, analiza, intelegerea datelor de business. Cursurile sunt sustinute de master black belti. Chiar daca organizatia Dvs are angajati incepatori in analiza datelor sau avansati in acest domeniu, sesiunea va acoperi tot ceea ce este necasar pentru a deveni un Minitab expert.

Nivel curs:

avansat

Durata curs:

3 zile

Cine poate participa:

Analisti de sistem, business analisti, belti six sigma, profesionisti in calitate, manageri de proiect, coordonatori de programe, leaderi, product manageri, executivi.

Curriculum :

DAY 1

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

1.4 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 Quiz: Normal Distribution

2.5 Summary

2.5.1 Objectives Review

DAY 2

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

3.3 1-Sample t-Test

3.3.1 Basic Concepts

3.3.6 Minitab Tools: 1-Sample t-Test

3.3.7 Exercise: 1-Sample t-Test

3.4  Variances Test

3.4.1 Basic Concepts

3.4.2 Boxplots

3.4.3 2 Variances Test Results 3.4.4 Assumptions

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

3.6 Paired t-Test

3.6.1 Basic Concepts

3.6.2 Individual Value Plots

3.6.3 Paired t-Test Results

3.7 1 Proportion Test

3.7.1 Basic Concepts

3.7.2 1 Proportion Test Results

3.8 Chi-Square Test

3.8.1 Basic Concepts

3.8.2 Chi-Square Test Results

3.9 Summary

3.9.1 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

4.3 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

4.4 Control Charts for Individual Observations

4.4.1 Basic Concepts

4.4.2 Moving Range Charts

4.4.3 Individuals Charts

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

4.6 Summary

4.6.1 Objectives Review

DAY 3

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 Testing for Normality

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

5.4 Process Capability for Nonnormal Data

5.4.1 Transformations and Alternate Distributions

5.5 Summary

5.5.1 Objectives Review

Chapter 6: Correlation and Regression

6.1 Introduction

6.1.1 Learning Objectives

6.2 Relationship Between Two Quantitative Variables

6.2.1 Basic Concepts

6.2.2 Scatterplot and Correlation

6.2.3 Correlation

6.3 Simple and Multiple Regression

6.3.1 Basic Concepts

6.4.1 Objectives Review

Chapter 7: Measurement Systems Analysis

7.1 Introduction

7.1.1 Learning Objectives

7.2 Basic Concepts

7.2.1 Accuracy and Precision

7.3 Repeatability and Reproducibility

7.3.1 Basic Concepts

7.3.2 Gage R&R Studies

7.4 Graphical Analysis of a Gage R&R Study

7.4.1 Basic Concepts (Components of Variation,

Xbar and R Charts, Interaction between Operator and Part, Comparative Plots

7.5 Attribute Agreement Analysis

7.5.1 Basic Concepts

7.6 Summary

7.6.1 Objectives Review

Chapter 8: Design of Experiments

8.1 Introduction

8.1.1 Learning Objectives

8.2 Factorial Designs

8.2.1 Creating and analyzing Full Factorial Designs

8.3 Fractional Factorial Designs

8.3.1 Basic Concepts

8.3.2 Creating and analyzing Fractional Factorial Designs

8.4 Summary

8.4.1 Objectives Review

RECAP and EXAM