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Decision Making01:20

Decision Making

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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: P-value Method01:09

Decision Making: P-value Method

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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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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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Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

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Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
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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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Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

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Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
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Related Experiment Video

Updated: Feb 25, 2026

Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases
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Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases

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Revisiting the Relationship Between Data, Models, and Decision-Making.

Ty P A Ferré1

  • 1Hydrology and Atmospheric Sciences, University of Arizona, 1133 E James E Rogers Way, Tucson, AZ 85721.

Ground Water
|August 10, 2017
PubMed
Summary
This summary is machine-generated.

Hydrologists can improve water resource decisions by using multiple, rival models instead of single predictions. This approach, including stakeholder advocacy models, clarifies risks and promotes better scientific decision-making.

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Area of Science:

  • Hydrology
  • Water Resource Management
  • Decision Science

Background:

  • Traditional hydrological approaches often rely on single-model predictions with quantitative uncertainties.
  • Water resource decision-makers frequently utilize qualitative, multiple-narrative frameworks.
  • A gap exists between scientific modeling outputs and the needs of decision-makers.

Purpose of the Study:

  • To advocate for a shift in hydrological practice towards supporting water resource decision-making more effectively.
  • To propose the development and use of rival model ensembles, including advocacy models.
  • To enhance the objective communication of risks to stakeholders.

Main Methods:

  • Developing ensembles of rival hydrological models.
  • Incorporating biased, advocacy models that represent stakeholder interests.
  • Analyzing the outcomes of using inclusive, multi-model approaches.

Main Results:

  • Rival model ensembles provide a clearer understanding of what is known, possible, and unknown in water resource systems.
  • Inclusive modeling platforms facilitate objective discussions about risks.
  • Stakeholder-inclusive models can lead to more appropriate applications of the scientific method.

Conclusions:

  • Adopting a multi-model, inclusive approach enhances the support hydrologists provide for water resource decisions.
  • The use of rival and advocacy models improves the clarity and relevance of scientific information for decision-makers.
  • This paradigm shift promotes more robust and scientifically grounded water resource management.