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.
Upon completion of this course participants will be able to:
- Explain the value of big data and analytics
- Discuss 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
- Distinguish between independent and dependent variables
- Describe methods of ensuring the quality of data
- Explain data management techniques including transforming data, recoding data, and handling missing data
- Identify some biases and errors data collection may be subject to
- Distinguish between correlation and causation
- Apply appropriate decision making techniques to a specific case
This course includes an “Ask the Expert” feature. You can use this feature to submit questions about course content. A subject matter expert will provide guidance or point you to additional resources for the topics you’re studying. Questions are answered as quickly as possible and usually within 24 hours.
Learners must achieve an average test score of at least 80% to meet the minimum successful completion requirement and qualify to receive IACET CEUs. Learners will have three attempts at all graded assessments.