Skip to content
# Data Analysis Practices

## Data Collection & Analysis Overview

#### MTA534

When you have finished this e-briefing, you will be able to: Explain the importance of data and data analysis in the journey from chaos to capability. Explain how data collection and analysis allows you to identify patterns of variation, suggest possible cause-effect relationships, clearly answer specific questions, and communicate results. Identify good practices for collecting, organizing, and analyzing data. Describe subsequent e-briefings and key topics related to data analysis. Click to Register
## Statistical Process Control

#### MTA535

When you have finished this e-briefing, you will be able to: Define statistical process control charts. Name and describe commonly used control charts: Individuals and Moving Range chart; X-bar and R-chart; and P-chart. Identify typical situations where each control chart can be used. Describe what significant patterns of variation look like. Identify when to seek support from other resources. Explain how statistical process control charts are used for analyzing data and for reducing process variation. Click to Register
## Cumulative Sum Charts

#### MTA536

When you have finished this e-briefing, you will be able to: Define the purpose of a Cumulative Sum Chart (also called “Cusum”, pronounced “cue sum”). Describe how to create a Cumulative Sum Chart. Explain how to interpret Cumulative Sum Charts. Describe typical applications of Cumulative Sum Charts using examples. Identify complex situations where you may need help from a statistician. Click to Register
## Techniques for Comparing Groups of Data

#### MTA537

When you have finished this e-briefing, you will be able to: Describe typical situations where it is necessary to compare groups of data. Describe different graphical methods for comparing groups of data. Explain how the graphical methods are used in process troubleshooting using examples. Identify commonly used quantitative methods for comparing groups of data. Identify complex situations where help should be sought. Click to Register
## Non-Graphical Data Analysis Techniques

#### MTA538

When you have finished this e-briefing, you will be able to: Define non-graphical data visualization techniques for analysis. Describe typical non-graphical data visualization techniques relevant for a manufacturing operation. Explain how non-graphical data visualization techniques are used to reveal patterns of variation. Identify situations where non-graphical data visualization techniques are most appropriate. Click to Register
## eAssessment

#### MTA539

Check your knowledge of this curriculum in this 20-question assessment. To complete this assessment, you must pass this assessment with a score of 80% or better, answering 16 of 20 questions correctly. Click to Register
## Data Analysis Practices ILT

#### MTA540