Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Group Design02:01

Group Design

9.3K
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
9.3K
Surveys02:16

Surveys

14.3K
Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
14.3K
Choosing Between z and t Distribution01:25

Choosing Between z and t Distribution

2.9K
The z and the Student t distribution estimate the population mean using the sample mean and standard deviation. However, to decide which distribution to use for a calculation, one needs to determine the sample size, the nature of the distribution, and whether the population standard deviation is known. If the population standard deviation is known and the population is normally distributed, or if the sample size is greater than 30, the z distribution is preferred. The Student t distribution is...
2.9K
Cluster Sampling Method01:20

Cluster Sampling Method

11.0K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
11.0K
Types of Selection01:46

Types of Selection

37.5K
Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
37.5K
Systematic Sampling Method01:17

Systematic Sampling Method

10.3K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
Systematic sampling is one of the simplest methods...
10.3K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Long-range mutual activation establishes Rho and Rac polarity during cell migration.

Nature cell biology·2026
Same author

A conserved antioxidant defense at the endoplasmic reticulum membrane.

Cell reports·2026
Same author

Arachidonic acid availability controls neutrophil swarm initiation and scaling.

bioRxiv : the preprint server for biology·2026
Same author

Many Cells Make Light Work: Self-Generated Gradients Organize <i>Dictyostelium</i> Aggregates and Neutrophil Swarms.

Cold Spring Harbor perspectives in biology·2026
Same author

Class-I myosin responds to changes in membrane tension during clathrin-mediated endocytosis in human induced pluripotent stem cells.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Investigating local negative feedback of Rac activity by mathematical models and cell-motility simulations.

iScience·2026

Related Experiment Video

Updated: May 3, 2026

Improving Student Outcomes with an Adaptable Molecular Cloning Course-Based Undergraduate Research Experience
10:17

Improving Student Outcomes with an Adaptable Molecular Cloning Course-Based Undergraduate Research Experience

Published on: November 15, 2024

1.8K

How should we be selecting our graduate students?

Orion D Weiner1

  • 1Cardiovascular Research Institute, Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA 94158.

Molecular Biology of the Cell
|February 15, 2014
PubMed
Summary

Years of research experience and subject GRE scores effectively predict graduate student success. Other common metrics like GPA and institution ranking do not reliably indicate performance. This study suggests refining graduate admissions criteria.

More Related Videos

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
07:34

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Published on: August 22, 2018

7.6K
Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
13:44

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

Published on: December 9, 2022

3.7K

Related Experiment Videos

Last Updated: May 3, 2026

Improving Student Outcomes with an Adaptable Molecular Cloning Course-Based Undergraduate Research Experience
10:17

Improving Student Outcomes with an Adaptable Molecular Cloning Course-Based Undergraduate Research Experience

Published on: November 15, 2024

1.8K
Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
07:34

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Published on: August 22, 2018

7.6K
Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
13:44

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

Published on: December 9, 2022

3.7K

Area of Science:

  • Biomedical Sciences
  • Graduate Education
  • Student Admissions

Background:

  • Universities commonly use undergraduate quantitative metrics for graduate student selection.
  • The predictive validity of these metrics for graduate success is often debated.
  • Identifying effective admissions criteria is crucial for optimizing student cohorts.

Purpose of the Study:

  • To identify undergraduate metrics that effectively discriminate between high- and low-performing graduate students.
  • To provide an unbiased analysis of admissions criteria used in the Tetrad program at UCSF.
  • To inform improvements in graduate admissions processes by highlighting predictive and non-predictive metrics.

Main Methods:

  • Retrospective analysis of highest- and lowest-ranked graduate students over 20 years.
  • Comparison of undergraduate metrics including research experience, GRE scores (subject, analytical, verbal, quantitative), GPA, and undergraduate institution ranking.
  • Statistical analysis to determine significant differences between performance groups.

Main Results:

  • Number of years of research experience was a strong positive predictor of graduate success.
  • Subject-specific Graduate Record Examinations (GREs) scores also significantly discriminated between high- and low-performing students.
  • Analytical, verbal, and quantitative GREs, GPA, and undergraduate institution ranking showed no significant correlation with graduate performance.

Conclusions:

  • Research experience and subject GREs are key indicators of graduate student potential.
  • Many commonly used admissions metrics may not be effective predictors of graduate success.
  • Institutions should conduct similar analyses to refine admissions processes and reduce reliance on non-predictive criteria.