1.6 Research questions

  • Normative (vs. empirical analytical), descriptive, causal and predictive research questions
    • Q: What is the difference?
  • Q: What does the “inference” in statistical inference stand for?

1.6.1 Research questions: Types

  • Normative vs. empirical analytical (positive)
    • Should men and women be paid equally? Are men and women paid equally (and why?)?
    • Q: Which one is empirical-analytical, which one normative? Can we derive hypotheses for normative questions?
  • What? vs. Why? (Gerring 2012, 722-723)
    • Describe aspect of the world vs. causal arguments that hold that one or more phenomena generate change in some outcome (imply a counterfactual)
    • My personal preference: descriptive vs. causal questions

1.6.2 Research questions: Descriptive (What?)

  • Measure:‘Would you say that most people can be trusted or that you can’t be too careful in dealing with people, if 0 means “Can’t be too careful” and 10 means “Most people can be trusted”?’

  • How are observations distributed across values of trust (Y)? (univariate)

Table 1.1: Univariate distribution of trust (2006)
0 1 2 3 4 5 6 7 8 9 10
303 42 172 270 369 1281 853 1344 1295 353 356
  • We can add as many variables/dimensions as we like → multivariate (e.g. gender, time)
    • Q: What would the table above look like when we add gender as a second dimension?
  • Descriptive questions (multivariate)
    • Do females have more trust than males?
    • Did trust rise across time?

1.6.3 Research questions: Causal (Why?)

Table 1.2: Joint distribution of trust and victimization (2006, N = 6633)
0 1 2 3 4 5 6 7 8 9 10
no victim 259 36 135 214 320 1142 782 1228 1193 326 331
victim 44 6 37 56 48 139 70 114 101 27 25
  • Mean Non-victims: 6.2; Mean Victims: 5.48
  • Descriptive questions: Do victims have a different/lower level of trust from/than non-victims?
  • Why?-questions start with difference(s) and, then, seek to explain why those difference(s) occured
    • Why does this group of people have a higher level of trust?
  • Causal questions: Is there a causal effect of victimization on trust? (We’ll define causal effect later)
  • Insights
    • Data underlying descriptive & causal questions is the same
    • Causal questions already concern one (or more) explanatory causal factors

1.6.4 Research questions: Predictive

  • Q: What does prediction look like?
  • Examples:
    • Can we predict trust with victimization?
    • Can we predict income with education?
    • Can we predict divorce with the number of children?
  • Quick summery…and more on that later!