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

Predicting Molecular Geometry02:27

Predicting Molecular Geometry

45.8K
VSEPR Theory for Determination of Electron Pair Geometries
45.8K
Prediction Intervals01:03

Prediction Intervals

3.4K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
3.4K
End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

1.2K
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
1.2K
Sensitivity, Specificity, and Predicted Value01:13

Sensitivity, Specificity, and Predicted Value

1.3K
In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
1.3K
Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

10.8K
Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
10.8K
Predicting Products: Substitution vs. Elimination02:52

Predicting Products: Substitution vs. Elimination

14.8K
When a nucleophile and an alkyl halide react, nucleophilic substitution and β-elimination reactions compete to generate products.
The following factors can influence the mechanisms competing against each other:
14.8K

You might also read

Related Articles

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

Sort by
Same author

Del Nido versus HTK cardioplegia for myocardial protection during adult complex valve surgery: a retrospective study.

BMC cardiovascular disorders·2021
Same author

Effect of an extrafibrillar dentin demineralization strategy on the durability of the resin-dentin bond.

Journal of the mechanical behavior of biomedical materials·2021
Same author

miR-141-3p regulates saturated fatty acid-induced cardiomyocyte apoptosis through Notch1/PTEN/AKT pathway via targeting PSEN1.

Environmental toxicology·2021
Same author

Fe<sub>3</sub>O<sub>4</sub>@polydopamine nanoparticle-loaded human umbilical cord mesenchymal stem cells improve the cognitive function in Alzheimer's disease mice by promoting hippocampal neurogenesis.

Nanomedicine : nanotechnology, biology, and medicine·2021
Same author

Preparation of Pseudo-typed H5 Avian Influenza Viruses with Calcium Phosphate Transfection Method and Measurement of Antibody Neutralizing Activity.

Journal of visualized experiments : JoVE·2021
Same author

Corrigendum: Xanthomatous Hypophysitis: A Case Report and Comprehensive Literature Review.

Frontiers in endocrinology·2021

Related Experiment Video

Updated: Feb 3, 2026

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

10.3K

Urban crime prediction based on spatio-temporal Bayesian model.

Tao Hu1,2,3,4, Xinyan Zhu1,2, Lian Duan4,5

  • 1State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China.

Plos One
|November 1, 2018
PubMed
Summary

This study developed a spatio-temporal Bayesian model to analyze urban burglary patterns. Results show crime rates correlate with population density and internet bar numbers, aiding urban safety strategies.

More Related Videos

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions
09:09

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions

Published on: November 23, 2015

9.1K
Spatio-Temporal Manipulation of Small GTPase Activity at Subcellular Level and on Timescale of Seconds in Living Cells
10:27

Spatio-Temporal Manipulation of Small GTPase Activity at Subcellular Level and on Timescale of Seconds in Living Cells

Published on: March 9, 2012

11.3K

Related Experiment Videos

Last Updated: Feb 3, 2026

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

10.3K
A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions
09:09

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions

Published on: November 23, 2015

9.1K
Spatio-Temporal Manipulation of Small GTPase Activity at Subcellular Level and on Timescale of Seconds in Living Cells
10:27

Spatio-Temporal Manipulation of Small GTPase Activity at Subcellular Level and on Timescale of Seconds in Living Cells

Published on: March 9, 2012

11.3K

Area of Science:

  • Epidemiology
  • Criminology
  • Spatial Statistics
  • Bayesian Modeling

Background:

  • Spatio-temporal Bayesian modeling is crucial for understanding disease patterns in epidemiology.
  • Urban crime analysis requires sophisticated methods to identify trends and contributing factors.
  • Existing models may not fully capture the dynamic nature of urban crime.

Purpose of the Study:

  • To develop a specialized spatio-temporal Bayesian model for analyzing urban crime.
  • To identify key socio-economic covariates influencing burglary rates in urban environments.
  • To analyze the spatio-temporal dynamics and trends of urban burglaries.

Main Methods:

  • Application of Bayesian theory to construct a spatio-temporal model tailored for urban crime.
  • Analysis of burglary data from Wuhan City (January-August 2013).
  • Inclusion and assessment of various socio-economic variables (population, internet bars, hotels, etc.).

Main Results:

  • The burglary crime rate in Wuhan City is significantly correlated with average resident population per community.
  • The number of local internet bars was identified as another significant covariate influencing burglary rates.
  • The model effectively analyzed spatio-temporal patterns and trends of burglaries.

Conclusions:

  • Population density and the prevalence of internet bars are key factors in urban burglary occurrences.
  • The developed spatio-temporal Bayesian model provides a scientific basis for urban safety planning.
  • Findings offer valuable insights for crime prevention and resource allocation in urban areas.