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Related Concept Videos

Decision Making01:20

Decision Making

250
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
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Decision Making: Traditional Method01:14

Decision Making: Traditional Method

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The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
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Reason and Intuition01:37

Reason and Intuition

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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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Heuristics01:21

Heuristics

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Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
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Decision Making: P-value Method01:09

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The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
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Manipulation and Analysis01:21

Manipulation and Analysis

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GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
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Integrating Visual Psychophysical Assays within a Y-Maze to Isolate the Role that Visual Features Play in Navigational Decisions
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A Typology of Decision-Making Tasks for Visualization.

Camelia D Brumar, Sam Molnar, Gabriel Appleby

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    Summary
    This summary is machine-generated.

    This study introduces a new typology for decision-making tasks in data visualization, categorizing them into CHOOSE, ACTIVATE, and CREATE. This framework aids in designing better decision-support tools and clarifies complex decision processes.

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    Area of Science:

    • Data Visualization
    • Human-Computer Interaction
    • Decision Science

    Background:

    • Data visualization aims to support decision-making, yet lacks specific task differentiation for complex decisions.
    • Existing taxonomies often focus on low-level analytical tasks, insufficient for designing decision-support tools.

    Purpose of the Study:

    • To introduce a concise typology of decision-making tasks (CHOOSE, ACTIVATE, CREATE) for the data visualization community.
    • To provide definitions suitable for visualization contexts and enable flexible description of complex decisions.

    Main Methods:

    • Iterative refinement of a decision-making task typology based on design goals from a literature review.
    • Validation through four case studies and semi-structured interviews with visualization experts.

    Main Results:

    • A three-task typology (CHOOSE, ACTIVATE, CREATE) was developed, offering hierarchical organization for complex decisions.
    • Case studies and expert interviews demonstrated the typology's descriptive capacity and effectiveness in analyzing decision processes.

    Conclusions:

    • The proposed typology enhances discourse between visualization designers and domain experts.
    • It offers a flexible framework for describing and designing decision-support systems in data visualization.