Measurement and Description

We begin our exploration of quantitative methods in sociology (and the social sciences more broadly) by thinking carefully about how we make the passage from theory and concepts to empirical data. For concepts to be explored empirically (not just theoretically), we need to operationalise them. The lecture introduces some core ideas behind social measurement in general. In the IT workshop, we will look more carefully at examples of how “social trust” has been conceptualised, operationalised and measured in practice.

Once empirical data have been collected, a first step in their analysis is to explore and describe the recorded variables using appropriate descriptive statistics. It may be that our research question is a very simple one and the whole purpose of the research was to describe the distribution of a measured concept or phenomenon. In most cases, however, descriptive statistics are but the first – albeit essential – step in the analytic process. In real-life research scenarios, we are more interested in drawing comparisons between cases and identifying associations (relationships) between various concepts and phenomena. That will be the topic of workshop 3.

Essential readings

Access links through Canvas - Newcastle University login required

1. Spiegelhalter (2020) The Art of Statistics:
   • CHAPTER 1 | Getting Things in Proportion: Categorical Data and Percentages
   • CHAPTER 2 | Summarizing and Communicating Numbers. Lots of Numbers
     • read until the section on Describing Relationships Between Variables
   • CHAPTER 3 | Why Are We Looking at Data Anyway? Populations and Measurement
     • recommended now, essential by Workshop 5
2. Goss-Sampson (2025) Statistical Analysis in JASP:
   • USING THE JASP ENVIRONMENT (pp. 2-7)
   • DATA HANDLING IN JASP (pp. 8-10)
   • JASP ANALYSIS MENU (pp. 12-15)
   • DESCRIPTIVE STATISTICS (pp. 15-21)
   • BASIC PLOTS (pp. 21-24)

Application:

• Bekkers & Sandberg (2019) Grading Generalized Trust Across Europe

Further readings

Statistics:

• Kranzler (2022) Statistics for the Terrified:
  • Section II: Describing Univariate Data (pp. 42-83)
• Çetinkaya-Rundel & Hardin (2024) Introduction to Modern Statistics:
  • Chapter 1 (“Data”)
  • Chapter 2 (“Study design”)
• Stevens, S. S. (1946) “On the Theory of Scales of Measurement.” Science 103(2684): 677–80.
• Duncan, Otis Dudley (1984) Notes on Social Measurement: Historical and Critical. New York: Russell Sage Foundation. (especially Chapter 4 discussing and criticising Stevens (1946))

On trust:

• Delhey, Jan, Kenneth Newton, and Christian Welzel (2011) “How General Is Trust in ‘Most People’? Solving the Radius of Trust Problem.” American Sociological Review 76(5): 786–807.
• Robbins, Blaine G. (2022) “Measuring Generalized Trust: Two New Approaches.” Sociological Methods & Research 51(1): 305–56.
• Robbins, Blaine G. (2024) “An Empirical Comparison of Four Generalized Trust Scales: Test–Retest Reliability, Measurement Invariance, Predictive Validity, and Replicability.” Sociological Methods & Research 53(2): 760–803.
• Uslaner, E. M. (2012) Chapter 7 (“Measuring generalized trust: in defense of the ‘standard’ question”, pp. 72-82) in Lyon, Fergus, Guido Möllering, and M. N. K. Saunders, eds. Handbook of Research Methods on Trust. Northampton, Mass: Edward Elgar Pub.