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

Ranks01:02

Ranks

Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
Levels of Organization01:09

Levels of Organization

Biological organization is the classification of biological structures, ranging from atoms at the bottom of the hierarchy to the Earth's biosphere. Each level of the hierarchy represents an increase in complexity that builds upon the previous level.
Molecules Are Composed of Atoms, and Biomolecules Are Assembled from Molecules:
The most basic levels include atoms, molecules, and biomolecules. Atoms, the smallest unit of ordinary matter, are composed of a nucleus and electrons. Molecules...
Ordinal Level of Measurement00:55

Ordinal Level of Measurement

The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks in the...
Orders of Magnitude01:15

Orders of Magnitude

The order of magnitude of a number is the power of 10 that most closely approximates it. Thus, the order of magnitude estimates the scale (or size) of its value. To find the order of magnitude of a number, take the base-10 logarithm of the number and round it to the nearest integer. Then the order of magnitude of the number is simply the resulting power of 10.
The order of magnitude is simply a way of rounding numbers consistently to the nearest power of 10. This makes doing rough mental math...
Quartile01:15

Quartile

Quartiles are numbers that separate the data into quarters. Quartiles may or may not be part of the data. To find the quartiles, first, find the median or second quartile. The first quartile, Q1, is the middle value of the lower half of the data, and the third quartile, Q3, is the middle value, or median, of the upper half of the data. To get the idea, consider the same data set:
1; 1; 2; 2; 4; 6; 6.8; 7.2; 8; 8.3; 9; 10; 10; 11.5
The median or second quartile is seven. The lower half of the...
Rate-Determining Steps03:08

Rate-Determining Steps

Relating Reaction Mechanisms
In a multistep reaction mechanism, one of the elementary steps progresses significantly slower than the others. This slowest step is called the rate-limiting step (or rate-determining step). A reaction cannot proceed faster than its slowest step, and hence, the rate-determining step limits the overall reaction rate.
The concept of rate-determining step can be understood from the analogy of a 4-lane freeway with a short-stretch of traffic-bottleneck caused due to...

You might also read

Related Articles

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

Sort by
Same author

Meeting the Challenge of Stigma.

Focus (American Psychiatric Publishing)·2025
Same author

Physician Mental Health: My Personal Journey and Professional Plea.

Academic medicine : journal of the Association of American Medical Colleges·2021
Same author

Leadership Development for Future Medical School Deans: Outcomes of the AAMC Council of Deans Fellowship Program.

Academic medicine : journal of the Association of American Medical Colleges·2020
Same author

In Reply to Patel et al.

Academic medicine : journal of the Association of American Medical Colleges·2020
Same author

Navigating Tumultuous Change in the Medical Profession: The Coalition for Physician Accountability.

Academic medicine : journal of the Association of American Medical Colleges·2019
Same author

Developing a Culture of Mentorship to Strengthen Academic Medical Centers.

Academic medicine : journal of the Association of American Medical Colleges·2019

Related Experiment Video

Updated: May 10, 2026

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
10:39

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

Published on: August 29, 2025

From rankings to mission.

Darrell G Kirch, John E Prescott

    Academic Medicine : Journal of the Association of American Medical Colleges
    |June 29, 2013
    PubMed
    Summary

    Medical school rankings often use inadequate data. New tools from the Association of American Medical Colleges (AAMC) offer objective data to assess unique institutional missions and improve training programs.

    Area of Science:

    • Medical Education
    • Higher Education Administration
    • Health Services Research

    Background:

    • Traditional school ranking systems, prevalent since the 1980s, often rely on insufficient data.
    • These rankings fail to capture the complex nature and unique contributions of institutions, particularly U.S. medical schools.
    • A study in Academic Medicine highlights the limitations of rankings for primary care training programs.

    Discussion:

    • Medical schools possess distinct missions, strengths, and community impacts that are poorly represented by subjective ranking methodologies.
    • The commentary emphasizes the need for objective data to guide institutional development in higher education.
    • The Association of American Medical Colleges (AAMC) is developing tools for comprehensive medical school assessment.

    Key Insights:

    Related Experiment Videos

    Last Updated: May 10, 2026

    Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
    10:39

    Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

    Published on: August 29, 2025

    • Each medical school's mission, strengths, and community impact are unique and not adequately reflected in current ranking systems.
    • Overly subjective ranking methodologies do not accurately represent the diverse contributions of medical schools.
    • Objective data is crucial for academic leaders to guide institutional development and improve training quality.

    Outlook:

    • The AAMC's Medical School Admissions Requirements and Missions Management Tool provide valid, applicable data for assessing medical schools.
    • These tools are being utilized by leaders to enhance institutional capacity and training programs.
    • There is a call for leaders in medical schools, teaching hospitals, and universities to adopt reliable data for continuous improvement in medical education and public health.