A 'sample' is not only a concept from statistics that has penetrated common sense but also a metaphor that has inspired much research and theorizing in current psychology. The sampling approach emphasizes the selectivity and the biases that are inherent in the samples of information input with which judges and decision makers are fed. As environmental samples are rarely random, or representative of the world as a whole, decision making calls for censorship and critical evaluation of the data given. However, even the most intelligent decision makers tend to behave like 'naive intuitive statisticians': quite sensitive to the data given but uncritical concerning the source of the data. Thus, the vicissitudes of sampling information in the environment together with the failure to monitor and control sampling effects adequately provide a key to re-interpreting findings obtained in the last two decades of research on judgment and decision making.

Research on human judgment and decision making has been strongly guided by a normative/descriptive approach, according to which human decision making is compared to the normative models provided by decision theory, statistics, and the probability calculus. A common empirical finding has been that human behavior deviates from the prescriptions by normative models--that judgments and decisions are subject to cognitive biases.
It is interesting to note that Swedish research on judgment and decision making made an early departure from this dominating mainstream tradition, albeit in two different ways. The "Neo-Brunswikian research" highlights the relationship between the laboratory task and the adaptation to a natural environment. The "process-tracing approach" attempts to identify the cognitive processes before, during, and after a decision. This volume summarizes current Swedish research on judgment and decision making, covering topics, such as dynamic decision making, confidence research, the search for dominance structures and differentiation, and social decision making.

Sampling approaches to judgment and decision making are distinct from traditional accounts in psychology and neuroscience. While these traditional accounts focus on limitations of the human mind as a major source of bounded rationality, the sampling approach originates in a broader cognitive-ecological perspective. It starts from the fundamental assumption that in order to understand intra-psychic cognitive processes one first has to understand the distributions of, and the biases built into, the environmental information that provides input to all cognitive processes. Both the biases and restriction, but also the assets and capacities, of the human mind often reflect, to a considerable degree, the irrational and rational features of the information environment and its manifestations in the literature, the Internet, and collective memory. Sampling approaches to judgment and decision making constitute a prime example of theory-driven research that promises to help behavioral scientists cope with the challenges of replicability and practical usefulness.

A 'sample' is not only a concept from statistics that has penetrated common sense but also a metaphor that has inspired much research and theorizing in current psychology. The sampling approach emphasizes the selectivity and the biases that are inherent in the samples of information input with which judges and decision makers are fed. As environmental samples are rarely random, or representative of the world as a whole, decision making calls for censorship and critical evaluation of the data given. However, even the most intelligent decision makers tend to behave like 'naive intuitive statisticians': quite sensitive to the data given but uncritical concerning the source of the data. Thus, the vicissitudes of sampling information in the environment together with the failure to monitor and control sampling effects adequately provide a key to re-interpreting findings obtained in the last two decades of research on judgment and decision making.

Research on human judgment and decision making has been strongly guided by a normative/descriptive approach, according to which human decision making is compared to the normative models provided by decision theory, statistics, and the probability calculus. A common empirical finding has been that human behavior deviates from the prescriptions by normative models--that judgments and decisions are subject to cognitive biases. It is interesting to note that Swedish research on judgment and decision making made an early departure from this dominating mainstream tradition, albeit in two different ways. The Neo-Brunswikian research highlights the relationship between the laboratory task and the adaptation to a natural environment. The process-tracing approach attempts to identify the cognitive processes before, during, and after a decision. This volume summarizes current Swedish research on judgment and decision making, covering topics, such as dynamic decision making, confidence research, the search for dominance structures and differentiation, and social decision making.

Sampling approaches to judgment and decision making are distinct from traditional accounts in psychology and neuroscience. While these traditional accounts focus on limitations of the human mind as a major source of bounded rationality, the sampling approach originates in a broader cognitive-ecological perspective. It starts from the fundamental assumption that in order to understand intra-psychic cognitive processes one first has to understand the distributions of, and the biases built into, the environmental information that provides input to all cognitive processes. Both the biases and restriction, but also the assets and capacities, of the human mind often reflect, to a considerable degree, the irrational and rational features of the information environment and its manifestations in the literature, the Internet, and collective memory. Sampling approaches to judgment and decision making constitute a prime example of theory-driven research that promises to help behavioral scientists cope with the challenges of replicability and practical usefulness.