PSC193 - Introduction to Data Analysis
Course Description
Combining intuition, experience and data into your decision-making process creates a powerful, balanced approach that leverages human insight with analytical rigor. This course focuses on different analytical methods, data quality and management, and visual representations of data. Explore research standards and best practices and learn strategies to overcome challenges when analyzing data. Gain insights to help you make decisions that are informed, confident and adaptable.
Learner Outcomes
After completing this course, you'll be able to:
- Explain the value of analytics for an organization and define key terms related to data analysis
- Explain the stages of the Davenport-Kim three-stage model for analysis
- Describe different data collection methods
- Differentiate between qualitative and quantitative data
- Explain standard analytical techniques
- Describe the characteristics of high-quality data
- Describe the elements of data management
- Identify possible biases and errors within a data set
- Describe different graphical displays for a data set
- Describe common challenges associated with data analysis
Upon completion of the course, learners may be eligible for:
- IACET CEUs: 0.5
- SHRM PDCs: 5
- PMI PDUs: 5
- 2 Ways of Working PDUs
- 2 Power Skills PDUs
- 1 Business Acumen PDU
- HRCI Credits: 5
Please Note:
Learners must achieve an average test score of at least 70% to meet the minimum successful completion requirement and qualify to receive IACET CEUs.
Notes
This course is offered through our curriculum partner, MindEdge, Inc. MindEdge was founded in 1998 by Harvard and MIT educators with a mission to improve the way the world learns. Since then, more than three million learners have participated in MindEdge programs.
Registered students will receive individualized communication with further instructions to help you prepare for class.