Classifying and Collecting Data

Six Sigma Yellow Belt    |    Intermediate
  • 14 videos | 1h 8m 51s
  • Includes Assessment
  • Earns a Badge
  • Certification CPE
Rating 4.4 of 508 users Rating 4.4 of 508 users (508)
This course covers business process improvement and data - specifically, how to collect it and classify it. Both of these are critical skills for process improvement. With this data, you can use Lean, Six Sigma, and Lean Six Sigma concepts and practices to measure and improve each stage of your process. This course introduces process control and the basic types of data, such as qualitative and quantitative data, as well as measurement scales. You will learn the elements of a data collection plan, and how to use data collection tools, such as surveys and checklists, to improve process design. This course is aligned to the ASQ Body of Knowledge, and is designed to assist Yellow Belt candidates toward achieving their certification.

WHAT YOU WILL LEARN

  • Recognize the role of data classification in a six sigma project
    Distinguish between examples of qualitative and quantitative data
    Distinguish between examples of continuous and discreet data
    Recognize types of measurement scales
    Identify characteristics of automated data collection
    Identify components of a data collection plan
    Identify principles of data sampling
  • Identify best practices for data collection
    Distinguish between influencing factors on the quality of data
    Distinguish between technologies used for data collection
    Identify benefits of using a survey as a data collection tool
    Identify benefits of using interviews for data collection
    Identify characteristics of an effective checklist used for data collection

IN THIS COURSE

  • 39s
  • 4m 6s
    Discover how to recognize the role of data classification in a Six Sigma project. FREE ACCESS
  • Locked
    3.  Qualitative and Quantitative Data
    3m 46s
    In this video, you will learn how to distinguish between examples of qualitative and quantitative data. FREE ACCESS
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    4.  Continuous and Discrete Data
    5m 4s
    During this video, you will learn how to distinguish between examples of continuous and discrete data. FREE ACCESS
  • Locked
    5.  Levels of Measurement
    5m 19s
    In this video, you will learn how to identify different types of measurement scales. FREE ACCESS
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    6.  Types of Data Collection
    4m 51s
    Learn how to identify characteristics of data collection that is automated. FREE ACCESS
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    7.  Contents of a Data Collection Plan
    6m 3s
    In this video, you will learn how to identify components of a data collection plan. FREE ACCESS
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    8.  Data Sources, Sampling, and Frequency
    6m 1s
    In this video, you will learn how to identify principles of data sampling. FREE ACCESS
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    9.  Data Collection Best Practices
    4m 47s
    Discover how to identify best practices for data collection. FREE ACCESS
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    10.  Avoiding Data Collection Problems
    5m 47s
    In this video, you will learn how to distinguish between factors that influence the quality of data. FREE ACCESS
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    11.  Using Information Technology for Data Collection
    5m 52s
    During this video, you will learn how to distinguish between technologies used for data collection. FREE ACCESS
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    12.  Using Surveys for Data Collection
    6m 11s
    In this video, find out how to identify the benefits of using a survey as a data collection tool. FREE ACCESS
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    13.  Using Interviews for Data Collection
    5m 12s
    Learn how to identify the benefits of using interviews for data collection. FREE ACCESS
  • Locked
    14.  Using Checklists for Data Collection
    5m 13s
    In this video, you will learn how to identify characteristics of an effective checklist for data collection. FREE ACCESS

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.

Digital badges are yours to keep, forever.

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