Measurement – Turning Concepts into Data

Go to Course: https://www.coursera.org/learn/measurement-turning-concepts-data

Introduction

# Course Review: Measurement – Turning Concepts into Data on Coursera ## Overview If you're looking to enhance your analytical skills, particularly in the realm of quantitative measurements, the Coursera course titled **"Measurement – Turning Concepts into Data"** is an outstanding choice. This course is designed for aspiring data analysts, social scientists, and researchers who seek to understand how to create and evaluate quantitative measures effectively. It focuses on critical concepts like health, educational attainment, and trust in government, which are often difficult to quantify. By the end of the course, you will be well-equipped with a robust toolkit for measuring complex concepts in a variety of contexts. ### Course Structure and Content The course is structured around four main modules: 1. **Fundamentals of Measurement**: The course kicks off with a thorough understanding of different types of measurement. You'll learn how to distinguish between qualitative and quantitative measures and understand how these measurements can be applied at both individual and aggregated levels. By the end of this module, you will appreciate the nuanced judgments that accompany statistical analyses. 2. **Building a Measurement Model**: Here, the focus shifts to the intricacies of measuring complex concepts. Using immigration policy as a case study, you'll delve into how various data points—such as financial resources, human resources, and outcome measures—can collectively provide insights into a multifaceted issue like border security. This module emphasizes the importance of conceptualization and operationalization, guiding you through the process of creating comprehensive measurement models. 3. **Survey Research**: This module tackles the challenges of measuring public opinion and behavior through surveys. You will learn about the foundational aspects of survey research, including sampling, design, and evaluation. A solid grasp of these principles is crucial for making informed decisions in both public and private sectors, as surveys serve as a critical means to gauge public sentiment and customer satisfaction. 4. **Evaluating Measurement Models**: Finally, comprehension of measurement errors is addressed. You'll learn how to evaluate your measurement tools and understand the impact of systematic and random measurement errors on reliability and validity. This knowledge is essential for ensuring that your analyses yield credible and actionable results. ## Who Should Enroll? This course is ideal for: - **Analysts** looking to improve their quantitative skills; - **Social scientists** aiming to gain insights into complex societal issues; - **Students** interested in research methods; - **Professionals** in government and business seeking to use data for decision-making. ## Personal Insights Having taken this course, I can confidently say that it not only enhances your technical skills but also enriches your understanding of the importance of measurement in research. The course is methodical and clear, with each module building on the last, which makes complex concepts easier to digest. The real-world examples, particularly in the immigration policy discussion, effectively illustrate measurement challenges and inspire critical thinking about data collection and interpretation. ## Recommendation I highly recommend **"Measurement – Turning Concepts into Data"** to anyone serious about analytics or research. The course supplies a strong foundational knowledge that will ensure you are well-prepared to tackle challenging measurement issues in your professional endeavors. Whether you’re looking to solidify your understanding of statistical measures or want to take your analytical capabilities to the next level, enrolling in this course could be one of the best decisions you make for your educational journey. Get ready to transform concepts into actionable data and elevate your analytical skills today!

Syllabus

Fundamentals of Measurement

Scientists and social science researchers are tasked with measuring concepts of all types. Some are quantitative, like blood pressure, while others are qualitative, like support for a policy proposal. Moreover, some measures are at the individual level while others are aggregated. This module will focus on distinguishing between different types of measures, different types of units and the advantages and disadvantages of these differences. By the end of this module, I think you'll better appreciate the amount of judgment and decision making that is required to perform a statistical analysis, an in particular, to create and select measure of the concepts you care about studying.

Researchers are often tasked with analyzing concepts that are difficult to measure. As an example, think about the issue of immigration. A full consideration of policies related to immigration requires analysts to measure concepts such as border security, competition for jobs and employer needs. While there is broad agreement in most governments about the need for border security, there is disagreement about the extent to which their borders are currently secure. How could you measure border security? You could collect data on the amount of money spent on border security, the number of border patrol agents, the amount of physical barriers in place, the apprehension rate of undocumented immigrants and the deportation rate of undocumented immigrants. Some of these measures are inputs while others are outputs. All of these measures capture some aspect of border security. Which measure would you use? Why is this the most appropriate measure? Could you use a combination of measures? This module will explore these questions by examining the measurement process. We'll discuss conceptualization, operationalization and how to create full measurement models based on operationalized concepts.

V. O. Key, a renowned public opinion scholar, wrote that “to speak with precision of public opinion is not unlike coming to grips with the Holy Ghost.” But although survey research is challenging, it is an essential tool in both government and business. Survey research allows researchers to measure opinion and behavior in a wide range of areas, build an understanding of how abstract concepts are perceived, develop and test theories of opinion formation and formulate policy recommendations. In the public sphere, surveys give public officials insight into the views of their constituents and allow citizens to hold their governing officials accountable. In the private sphere, companies use surveys to measure their customers' experiences and levels of satisfaction with goods and services. This module will cover the three fundamental pillars of survey research: sampling, design and evaluation.

After you have designed a measurement tool, whether it is a survey, test, data collection technique or some other approach, it is essential to evaluate that tool. It is inevitable that a measurement tool will suffer from some degree of measurement error. If the error is well-understood and not overwhelmingly large, there are statistical techniques a researcher can use to address that error in an analysis. This module will introduce the concepts of systematic and random measurement error and explore how this error affects the reliability and validity of a measurement tool.