Introduction to Data Analysis

Whatever your profession. Whatever your field. As a professional, and certainly as a leader, you will be asked to make a decision based on data. This course will introduce the different types of decisions made in an organizational setting, why quantitative analytics is important, and how data quality can affect decision making. Since quantitative analytics is used in various settings, this intermediate-level course also offers insight into how research is used in different sectors. From a management perspective, the course highlights appropriate quantitative methods and ways to ensure quality and accuracy through research design.

Learning Outcomes

• Explain why quantitative analysis and analytics is important in decision making
• Explain the types of decisions that can be made analytically in an organizational setting
• Describe different decision making models and tools
• Identify the fundamental concepts of measurement including levels of measurement, reliability and validity, errors, measurement and information bias
• Explain how quality data affects decision making (GIGO principle)
• Describe methods of ensuring the quality of data
• Evaluate techniques for ensuring accurate research design
• Describe how research is used in different settings: business, education, health care, the military, government, nonprofits
• Explain data management techniques including transforming data, recoding data, and handling missing data
• Apply appropriate decision making techniques to a specific case

Key Features

•  Expert-supported
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•  Mobile-friendly
•  Accessible
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•  Badge and credit-awarding
•  Games & Flashcards
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•  Video content
•  Real-world case studies
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•  Audio-enabled in app

Notes

This course has an "Ask the Expert" feature, which submits your questions directly to an expert in the field you are studying. Questions are answered as quickly as possible and usually within 24 hours.

This course does not require any additional purchases of supplementary materials.

Learners must achieve an average test score of at least 70% to meet the minimum successful completion requirement and qualify to receive IACET CEU credit. Learners will have three attempts at all graded assessments.

Project Management Institute, PMI, the Registered Education Provider logo, Project Management Professional, PMP, Project Management Body of Knowledge, PMBOK, PMI Agile Certified Practitioner, PMI-ACP, PMI Risk Management Professional, PMI-RMP, the PMI Talent Triangle, and the PMI Talent Triangle logo are marks of the Project Management Institute, Inc.

Information in this course has been taken from A Guide to the Project Management Body of Knowledge, (PMBOK®Guide) — Sixth Edition, Project Management Institute Inc., 2017.