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

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...
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...
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
Understanding Deception01:14

Understanding Deception

Deception is a pervasive aspect of human communication. Empirical studies have shown that most individuals engage in some form of deceit on a daily basis, with approximately 20% of social exchanges involving deceptive elements. Lying follows a developmental trajectory, peaking during adolescence and declining with age, possibly due to the maturation of cognitive control and social accountability.Cognitive and Social Factors in Deception DetectionDespite its prevalence, accurately detecting...
Errors occurring during blood pressure monitoring01:25

Errors occurring during blood pressure monitoring

Blood pressure monitoring is a crucial clinical procedure in diagnosing and managing various cardiovascular conditions. Despite its significance, the accuracy of blood pressure measurements can be compromised by multiple factors, potentially leading to either falsely high or low readings. These inaccuracies are critical as they can significantly impact patient care. So, it is vital to understand these challenges deeply and adopt strategic approaches to minimize errors.
Several factors...

You might also read

Related Articles

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

Sort by
Same author

Assessment of psychological and physiological responses to auditory and visual stimuli during recovery from acute stress induction.

Physiology international·2026
Same author

Occupational distress factors associated with suicidal ideation among physicians and comparison with other US workers.

Academic medicine : journal of the Association of American Medical Colleges·2026
Same author

Crisis-Related Self-Reported symptoms of posttraumatic stress disorder in graduate medical education trainees: Results from a Multi-Institutional study.

Academic medicine : journal of the Association of American Medical Colleges·2026
Same author

Associations of spousal support with career attrition in academic medicine: a multi-specialty cross-sectional survey study.

BMJ leader·2026
Same author

Associations and Differences Between Occupational Burnout and Depression in Large Studies of U.S. Physicians.

Academic medicine : journal of the Association of American Medical Colleges·2026
Same author

The validation of measured and self-reported sleep duration and perceived sleep quality: an empirical study with three generations of smartwatches.

Frontiers in psychiatry·2026

Related Experiment Video

Updated: May 15, 2026

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime
07:36

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime

Published on: May 3, 2016

5 ways statistics can fool you--tips for practicing clinicians.

Colin P West1, Denise M Dupras

  • 1Division of General Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN, United States. west.colin@mayo.edu

Vaccine
|December 19, 2012
PubMed
Summary

Clinicians can improve patient care by understanding five key statistical concepts for interpreting medical research. Applying these principles helps in evaluating research findings more effectively, especially from vaccine studies.

Related Experiment Videos

Last Updated: May 15, 2026

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime
07:36

An Experimental Analysis of Children's Ability to Provide a False Report about a Crime

Published on: May 3, 2016

Area of Science:

  • Medical Research Methodology
  • Clinical Epidemiology
  • Biostatistics

Background:

  • Many clinicians struggle to critically evaluate and apply medical research findings to patient care.
  • The increasing volume of medical literature presents a challenge for evidence-based practice.

Purpose of the Study:

  • To introduce and illustrate five fundamental statistical concepts crucial for interpreting medical literature.
  • To enhance clinicians' ability to apply research findings to patient care, using vaccine literature examples.

Main Methods:

  • Discussion of five core statistical principles relevant to medical literature interpretation.
  • Illustration of concepts using practical examples from vaccine research.

Main Results:

  • Separate consideration of clinical versus statistical significance is vital.
  • Absolute risks provide more practical information than relative risks.
  • Confidence intervals offer more nuanced data than p-values.
  • Caution is needed with isolated significant p-values amid multiple testing.
  • Statistically nonsignificant results do not rule out clinically important effects.

Conclusions:

  • Mastering these statistical concepts empowers clinicians to better interpret medical research.
  • Improved interpretation of medical literature can lead to more informed clinical decision-making and enhanced patient care.