This course provides a framework for how analysts can create and evaluate quantitative measures. Consider the many tricky concepts that are often of interest to analysts, such as health, educational attainment and trust in government. This course will explore various approaches for quantifying these concepts. The course begins with an overview of the different levels of measurement and ways to transform variables. We’ll then discuss how to construct and build a measurement model. We’ll next examine surveys, as they are one of the most frequently used measurement tools. As part of this discussion, we’ll cover survey sampling, design and evaluation. Lastly, we’ll consider different ways to judge the quality of a measure, such as by its level of reliability or validity. By the end of this course, you should be able to develop and critically assess measures for concepts worth study. After all, a good analysis is built on good measures.
About this Course
Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
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TOP REVIEWS FROM MEASUREMENT – TURNING CONCEPTS INTO DATA
Very well presented. Readings came from a variety of sources, exposing the learner to sites where we can continue to learn more about this topic.
Participation in this course has deepened my understanding of measuring concepts in ways I never thought possible
This course taught me how to do research methods in my research projects.
Note that the reading for week 4, Validity, requires a puchase to access
About the Data Literacy Specialization
This specialization is intended for professionals seeking to develop a skill set for interpreting statistical results. Through four courses and a capstone project, you will cover descriptive statistics, data visualization, measurement, regression modeling, probability and uncertainty which will prepare you to interpret and critically evaluate a quantitative analysis.
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