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The Anchoring-and-Adjustment Heuristic01:25

The Anchoring-and-Adjustment Heuristic

In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the $2,000...
Hindsight Biases01:12

Hindsight Biases

Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now?
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Decision Making: P-value Method

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 have a...
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Decision Making: Traditional Method

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...
Bias01:22

Bias

Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
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Motivational Bias

Cognitive bias results from limitations in thinking and information processing, leading to systematic errors in judgment. Conversely, motivational bias stems from personal desires or emotions, causing distortions in perception to align with self-interest. Motivational bias influences how individuals perceive and attribute causes to events, often shaped by personal needs, goals, and self-esteem preservation. This bias can distort judgment, leading to inaccurate assessments of success, failure,...

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Video Experimental Relacionado

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Combining Behavioral Endocrinology and Experimental Economics: Testosterone and Social Decision Making
11:51

Combining Behavioral Endocrinology and Experimental Economics: Testosterone and Social Decision Making

Published on: March 2, 2011

NOBEL DE ECONOMÍA: Cómo lidiar con los sesgos y las elecciones discretas.

C Seife

    Science (New York, N.Y.)
    |September 11, 2007
    PubMed
    Resumen

    Dos investigadores ganaron el Premio Nobel de Ciencias Económicas por desarrollar nuevas herramientas microeconómicas. Su trabajo proporciona métodos para analizar datos imperfectos y comprender el comportamiento económico individual, especialmente con respecto al sesgo de selección y las elecciones discretas.

    Área de la Ciencia:

    • Economía La economía es la economía.
    • La microeconomía es la microeconomía.
    • La econometría es la econometría.

    Sus antecedentes:

    • El estudio del comportamiento económico individual a menudo implica datos imperfectos.
    • La extracción de conclusiones a partir de estos datos presenta desafíos metodológicos significativos.

    Objetivo del estudio:

    • Reconocer los avances en las herramientas microeconómicas para el análisis de datos imperfectos.
    • Para resaltar nuevos enfoques para el manejo de sesgo de selección y la cuantificación de opciones discretas.

    Principales métodos:

    • James Heckman desarrolló métodos para abordar el sesgo de selección en los datos económicos.
    • Daniel McFadden creó técnicas para cuantificar las elecciones individuales discretas.

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    Principales resultados:

    • Se han proporcionado nuevas herramientas analíticas al campo de la microeconomía.
    • Mejora de la capacidad para sacar conclusiones de datos con imperfecciones inherentes.

    Conclusiones:

    • La investigación premiada avanzó significativamente las metodologías dentro de la microeconomía.
    • Estos avances ofrecen marcos robustos para comprender el comportamiento económico con datos limitados o sesgados.