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Related Concept Videos

Quantitative Analysis01:12

Quantitative Analysis

Quantitative analysis is a technique for measuring the amount of specific constituents in a sample. When the sample's composition is unknown, qualitative analysis is performed first to identify its components, which ensures that the correct substances are measured during the quantitative phase.
In quantitative analysis, two key measurements are made: the sample quantity and a property proportional to the amount of the analyte (the substance being analyzed). This forms the basis of the method...
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Quantifying Work02:30

Quantifying Work

As a system undergoes a change, its internal energy can change, and energy can be transferred from the system to the surroundings, or from the surroundings to the system.
The Scientific Method02:40

The Scientific Method

Research is what makes the difference between facts and opinions. Facts are observable realities, and opinions are personal judgments, conclusions, or attitudes that may or may not be accurate. In the scientific community, facts can be established only using evidence collected through empirical research.

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A Quantitative Fitness Analysis Workflow
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Published on: August 13, 2012

Ramifications of increased training in quantitative methodology.

Herbert Zimiles1

  • 1Arizona State University, USA. zimiles@asu.edu

The American Psychologist
|February 13, 2009
PubMed
Summary

This commentary addresses gaps in doctoral psychology training. It emphasizes how quantitative methodology advancements impact student choices and research topics.

Area of Science:

  • Psychology
  • Quantitative Methodology
  • Doctoral Education

Background:

  • The article by Aiken, West, and Millsap identified significant deficiencies in doctoral training for statistics, measurement, and methodology within psychology programs.
  • This led to a call for expanded graduate instruction resources and programs to address these identified gaps.

Discussion:

  • This comment extends the discussion by posing critical questions regarding the implications of these training deficiencies.
  • It highlights the need to consider how advancements in quantitative analysis training influence the field's future.

Key Insights:

  • Advances in quantitative methodology training are crucial for addressing existing gaps in psychological research.
  • The expansion of graduate instruction in these areas is essential for maintaining scientific rigor.

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Outlook:

  • Future research should investigate how evolving quantitative training impacts student recruitment and research trends in psychology.
  • Greater attention is needed on the interplay between methodological training and the direction of psychological inquiry.