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Related Concept Videos

Mathematical Modeling: Problem Solving01:29

Mathematical Modeling: Problem Solving

Mathematical modeling transforms real-world scenarios into mathematical expressions, allowing for structured problem-solving and analysis. This process involves defining the situation, assigning variables to measurable quantities, selecting an appropriate model, and solving the resulting equation. Such models are invaluable in finance, providing precise methods to evaluate investments, loans, and repayment structures.A widely used example is the calculation of fixed monthly payments on a loan,...
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Multiple Bar Graph

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Stereotype Threat and Self-fulfilling Prophecies02:09

Stereotype Threat and Self-fulfilling Prophecies

When we hold a stereotype about a person, we have expectations that he or she will fulfill that stereotype. A self-fulfilling prophecy is an expectation held by a person that alters his or her behavior in a way that tends to make it true. When we hold stereotypes about a person, we tend to treat the person according to our expectations. This treatment can influence the person to act according to our stereotypic expectations, thus confirming our stereotypic beliefs. Research by Rosenthal and...
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One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:

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Related Experiment Video

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Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics (BM-PROMA)
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Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics (BM-PROMA)

Published on: August 28, 2021

Sex Differences in Math-Intensive Fields.

Stephen J Ceci1, Wendy M Williams

  • 1Cornell University.

Current Directions in Psychological Science
|December 15, 2010
PubMed
Summary
This summary is machine-generated.

Women are underrepresented in math-intensive STEM fields. This study finds that career preferences and lifestyle choices, influenced by both free will and external constraints, are the primary drivers of this disparity.

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Area of Science:

  • STEM
  • Mathematics
  • Psychology
  • Sociology
  • Economics
  • Education

Background:

  • Women have made employment gains in many scientific fields.
  • Underrepresentation persists in fields demanding significant mathematical skills.

Purpose of the Study:

  • To explore reasons for women's underrepresentation in math-intensive STEM careers.
  • To synthesize interdisciplinary findings on this complex issue.

Main Methods:

  • Literature synthesis across psychology, endocrinology, sociology, economics, and education.
  • Analysis of potential factors: ability gaps, discrimination, and career/lifestyle choices.

Main Results:

  • While ability gaps and discrimination play a role, they are not the primary drivers.
  • Sex differences in career preferences and lifestyle choices are the most significant factor.

Conclusions:

  • Women's underrepresentation in math-intensive STEM fields is primarily due to differences in career preferences and lifestyle choices.
  • These preferences and choices are shaped by a combination of free decisions and societal/external constraints.