The discipline of sociology focuses on interactions and group processes from the perspective of emergent phenomena at the social level. Concepts like social embedding, norms, group-level motivation, or status hierarchies can only be defined and conceptualized in contexts in which individuals are involved in social interaction. Such concepts share the property of being social facts that cannot be changed by individual intention alone and that require some element of individual adjustment to the socially given condition. Sociologists study the embeddedness of individual motivations or preferences in the context of social phenomena as such and the impact of these phenomena on individual adaptation. However, these phenomena can only be observed in individual human behavior, and this tension between the substantive focus on the aggregate level and the analytical focus on the individual level is the challenge that sociological experiments confront.

In the introduction, the field of experimental sociology is outlined and the core concepts of manipulation and control, as well as two crucial conditions of control, are introduced. The random allocation of participants to the treatment and the control group ensures that exogenous factors are distributed equally across these groups, which allows to evaluate the effect of the manipulated condition. Incentivization helps operationalizing behavioral assumptions into the experimental condition. The chapter then briefly elaborates on the topics of the following chapters.

This chapter summarizes the main points of the book and reflects on possible ways ahead for experimental sociology.

Laboratory experiments are the type of study that most people have in mind when talking about experiments. In this chapter, we first discuss the strengths of laboratory experiments, which offer the highest degree of experimental control as compared to other types of experiments. Single factors can be manipulated according to the requirements of theories under highly controlled conditions. As such, laboratory experiments are well-placed to test theories. We then introduce a sociological laboratory experiment as a leading example, which we use as a reference for a discussion of several principles of laboratory research. Furthermore, we discuss a second goal of laboratory experiments, which is the establishment of empirical regularities in situations where theory does not provide sufficient guidance for deriving behavioral expectations. The chapter concludes with a short discussion of caveats for the analysis of sociological data generated in laboratory experiments.

Vignette experiments are vignettes are brief descriptions of social objects including a list of varying characteristics, on the basis of which survey respondents state their evaluations or judgments. The respondents’ evaluations typically concern positive beliefs, normative judgments, or their own intentions or actions. Using a study on the gender pay gap and an analysis of trust problems in the purchase of used cars as examples, we discuss the design characteristics of vignettes. Core issues are the selection of the vignettes that are included out of the universe of possible combinations, the type of dependent variables, such as rating scales or ranking tasks, the presentation style, differentiating text vignettes from a tabular format, and issues related to sampling strategies.

This chapter addresses the often-misunderstood concept of validity. Much of the methodological discussion around sociological experiments is framed in terms of internal and external validity. The standard view is that the more we ensure that the experimental treatment is isolated from potential confounds (internal validity), the more unlikely it is that the experimental results can be representative of phenomena of the outside world (external validity). However, other accounts describe internal validity as a prerequisite of external validity: Unless we ensure internal validity of an experiment, little can be said of the outside world. We contend in this chapter that problems of either external or internal validity do not necessarily depend on the artificiality of experimental settings or on the laboratory–field distinction between experimental designs. We discuss the internal–external distinction and propose instead a list of potential threats to the validity of experiments that includes "usual suspects" like selection, history, attrition, and experimenter demand effects and elaborate on how these threats can be productively handled in experimental work. Moreover, in light of the different types of experiments, we also discuss the strengths and weaknesses of each regarding threats to internal and external validity.

The first sociological experiments have been conducted in the second and third decades of the twentieth century, accompanied by a fierce debate about the possibilities and limits of the approach, which anticipated many of the critiques currently raised against the method. The chapter traces the development of experimental research in sociology from these beginning to modern perspectives. One of the reasons for the marginal position of experimentation in sociology has been the reluctance to give up full control of potentially intervening variables (called the ex post facto method) in favor of randomization. Inspirations from social psychology and, later, economics, have finally resulted in the experimental designs that are currently used in sociology.

Vignette experiments are a tool to present systematically varied descriptions of traits and conditions and eliciting to survey respondent and to elicit their beliefs and normative judgments on different combinations of these traits and conditions. Using a study on the gender pay gap and an analysis of trust problems in the purchase of used cars as examples, we discuss design characteristics of vignettes. Core issues are the selection of the vignettes that are included out of the universe of possible combinations, the type of dependent variables, such as rating scales or ranking tasks, the presentation style, differentiating text vignettes from a tabular format, and issues related to sampling strategies.

In Chapter 3 we learned how to do basic probability calculations and even put them to use solving some fairly complicated probability problems. In this chapter and the next two, we generalize how we do probability calculations, where we will transition from working with sets and events to working with random variables.

To do statistics you must first be able to “speak probability.” In this chapter we are going to concentrate on the basic ideas of probability. In probability, the mechanism that generates outcomes is assumed known and the problems focus on calculating the chance of observing particular types or sets of outcomes. Classical problems include flipping “fair” coins (where fair means that on one flip of the coin the chance it comes up heads is equal to the chance it comes up tails) and “fair” dice (where fair now means the chance of landing on any side of the die is equal to that of landing on any other side).

In Chapter 5 we learned about a number of discrete distributions. In this chapter we focus on continuous distributions, which are useful as models of various real-world events. By the end of this chapter you will know nine continuous and eight discrete distributions. There are many more continuous distributions, but these nine will suffice for our purposes. These continuous distributions are useful for modeling various types of processes and phenomena that are encountered in the real world.