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

Time-Series Graph00:54

Time-Series Graph

A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
Interpreting Run Charts01:25

Interpreting Run Charts

Run charts, essentially line graphs plotted over time, serve as fundamental yet effective tools for process analysis. They chronicle data sequentially, facilitating the identification of trends, shifts, or cyclical movements. This graphical representation is instrumental in determining whether a process is stable or exhibits signs of potential instability indicative of special cause variation. In the healthcare domain, run charts depict infection rates over time, enabling hospitals to monitor...
Scatter Plot01:15

Scatter Plot

The most common and easiest way to display the relationship between two variables, x and y, is a scatter plot. A scatter plot shows the direction of a relationship between the variables. A clear direction happens when there is either:
Drug Concentration Versus Time Correlation01:15

Drug Concentration Versus Time Correlation

The plasma drug concentration-time curve is a crucial tool in pharmacokinetics, representing the drug's concentration in plasma at different time intervals post-administration. This curve illustrates the drug's journey from absorption into the systemic circulation, distribution to body tissues, and eventual elimination through excretion or biotransformation.
Two pivotal parameters are the minimum effective concentration (MEC) and the minimum toxic concentration (MTC). The MEC is the lowest drug...
Central Tendency: Analysis01:10

Central Tendency: Analysis

Measures of central tendency are tools used in biostatistics to identify the average or center of a dataset. They offer a single representative value for understanding and summarizing data distribution.
The mean is one such measure, calculated by totaling all values in a dataset and dividing by the number of values. For instance, the mean blood pressure reading (120, 130, 140, 150) would be 135. However, the mean can be affected by extreme values or outliers.
The median, another measure,...
Variability: Analysis01:11

Variability: Analysis

Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...

You might also read

Related Articles

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

Sort by
Same author

Antibody-drug conjugate-related marker heterogeneity between primary tumors and metastatic lymph nodes in advanced urothelial cancers.

Journal of translational internal medicine·2026
Same author

Avian Foxp3 acts as a switch for IL-10 by directly binding the T3G motif: revealing a novel epigenetic modulation paradigm.

Cell communication and signaling : CCS·2026
Same author

Interfacial Engineering of Dry-Processed High-Loading LiNi<b><sub>0.5</sub></b>Mn<b><sub>1.5</sub></b>O<b><sub>4</sub></b> Cathodes: Additive Dissolution and Bilayer Cathode-Electrolyte Interphase toward Stable High-Voltage Lithium Metal Batteries.

ACS applied materials & interfaces·2026
Same author

Circulating IL-17 a as a downstream inflammatory indicator of depression: Insights from mendelian randomization and animal experiments.

Cytokine·2026
Same author

Overexpression of SLC44A4 suppresses ferroptosis and reduces lipid peroxidation <i>via</i> noncanonical NF-κB signaling in a NIK-dependent manner.

Annals of medicine·2026
Same author

Cyanobacterial extracellular polymeric substances empowered biological aqua crust formation via selective mineral adsorption for sustainable metal(loid) bioremediation.

Journal of hazardous materials·2026
Same journal

FGO-SLAM++: Real-time Geometry-Aware Gaussian SLAM with Continuous Opacity Field.

IEEE transactions on visualization and computer graphics·2026
Same journal

Blue Noise Dithering for Reservoir-based Spatio-temporal Importance Resampling.

IEEE transactions on visualization and computer graphics·2026
Same journal

ROS-GS: Relightable Outdoor Scenes With Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2026
Same journal

MesoSplats: Texture Synthesis with Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2026
Same journal

GLLA: A Unified Force-Directed Graph Layout Framework Supporting Local Adjustments.

IEEE transactions on visualization and computer graphics·2026
Same journal

Multi-Perception Crowd: Learning to combine entity and implicit perception for diverse crowd simulation.

IEEE transactions on visualization and computer graphics·2026
See all related articles

Related Experiment Video

Updated: Jun 19, 2026

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

SellTrend: inter-attribute visual analysis of temporal transaction data.

Zhicheng Liu1, John Stasko, Timothy Sullivan

  • 1School of Interactive Computing, GVU Center, Georgia Institute of Technology, USA. zliu6@gatech.edu

IEEE Transactions on Visualization and Computer Graphics
|October 17, 2009
PubMed
Summary
This summary is machine-generated.

We developed SellTrend, a visualization tool helping analysts understand complex airline purchase data. This system aids in identifying factors contributing to failed transactions, improving data analysis for business intelligence.

More Related Videos

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

Related Experiment Videos

Last Updated: Jun 19, 2026

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

Area of Science:

  • Data Visualization
  • Business Intelligence
  • Human-Computer Interaction

Background:

  • Analyzing multi-variate temporal and categorical event sequences is challenging.
  • Identifying complex attribute combinations leading to failed transactions requires sophisticated tools.

Purpose of the Study:

  • To present the design and utility of SellTrend, a novel visualization system.
  • To address the challenge of analyzing complex airline travel purchase request data.

Main Methods:

  • SellTrend integrates time series visualization, faceted browsing, and historical trend analysis.
  • The system visualizes multi-variate, temporally driven transaction data.

Main Results:

  • SellTrend aids analysts in identifying complex combinations of attributes linked to failed purchase requests.
  • Initial user feedback confirms the system's utility and benefits for data analysis.

Conclusions:

  • SellTrend offers an innovative approach to analyzing complex transaction data.
  • The visualization system demonstrates effectiveness in identifying key factors in failed purchase requests.