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

Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

609
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
609
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

18.8K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
18.8K
Comparative Excretory Systems02:24

Comparative Excretory Systems

26.7K
Animals have evolved different strategies for excretion, the removal of waste from the body. Most waste must be dissolved in water to be excreted, so an animal’s excretory strategy directly affects its water balance.
26.7K
Comparing Experimental Results: Student's t-Test01:09

Comparing Experimental Results: Student's t-Test

6.1K
The t-test is a statistical method used to compare the sample mean with a population mean or compare two means from two data sets. The test statistic is calculated from the standard deviation, mean, and number of measurements in the data set at a selected confidence interval and then compared to a table of critical values at this confidence level. If the test statistic is smaller than the critical value, the null hypothesis is accepted. In this case, we state that the difference between the...
6.1K
Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes02:16

Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes

16.5K
The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...
16.5K
Comparing Intermolecular Forces: Melting Point, Boiling Point, and Miscibility02:34

Comparing Intermolecular Forces: Melting Point, Boiling Point, and Miscibility

51.7K
Intermolecular forces are attractive forces that exist between molecules. They dictate several bulk properties, such as melting points, boiling points, and solubilities (miscibilities) of substances. Molar mass, molecular shape, and polarity affect the strength of different intermolecular forces, which influence the magnitude of physical properties across a family of molecules.
Temporary attractive forces like dispersion are present in all molecules, whether they are polar or nonpolar. They...
51.7K

You might also read

Related Articles

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

Sort by
Same author

Opposing-through crash risk forecasting using artificial intelligence-based video analytics for real-time application: integrating generalized extreme value theory and time series forecasting models.

Accident; analysis and prevention·2025
Same author

A before-after safety evaluation of wide centerline treatment considering the simultaneous changes in lane width and sealed shoulder width.

Accident; analysis and prevention·2025
Same author

A game theoretical model to examine pedestrian behaviour and safety on unsignalised slip lanes using AI-based video analytics.

Accident; analysis and prevention·2025
Same author

Examining collision avoidance behavior of distracted drivers: A correlated grouped random parameters accelerated failure time model with heterogeneity-in-means.

Accident; analysis and prevention·2025
Same author

Influence of road safety policies on the long-term trends in fatal Crashes: A Gaussian Copula-based time series count model with an autoregressive moving average process.

Accident; analysis and prevention·2024
Same author

Gap acceptance behaviour and crash risks of mobile phone distracted young drivers at roundabouts: A random parameters survival model.

Accident; analysis and prevention·2024

Related Experiment Video

Updated: Feb 8, 2026

Lipidico Injection Protocol for Serial Crystallography Measurements at the Australian Synchrotron
07:28

Lipidico Injection Protocol for Serial Crystallography Measurements at the Australian Synchrotron

Published on: September 23, 2020

3.7K

User satisfaction with train fares: A comparative analysis in five Australian cities.

Puteri Paramita1, Zuduo Zheng2, Md Mazharul Haque1

  • 1School of Civil Engineering & Built Environment, Science and Engineering Faculty, Queensland University of Technology, Brisbane, Queensland, Australia.

Plos One
|June 22, 2018
PubMed
Summary

Passenger satisfaction with train fares varies by gender, origin city, and travel method. Fare structures and waiting times significantly impact perceived value, influencing rider loyalty in Australian public transport.

More Related Videos

A User-friendly and Powerful R Analysis of Large-scale Datasets
10:56

A User-friendly and Powerful R Analysis of Large-scale Datasets

Published on: November 4, 2025

379
Breakfast Habits among Schoolchildren in the City of Uruguaiana, Brazil
06:48

Breakfast Habits among Schoolchildren in the City of Uruguaiana, Brazil

Published on: July 29, 2020

5.2K

Related Experiment Videos

Last Updated: Feb 8, 2026

Lipidico Injection Protocol for Serial Crystallography Measurements at the Australian Synchrotron
07:28

Lipidico Injection Protocol for Serial Crystallography Measurements at the Australian Synchrotron

Published on: September 23, 2020

3.7K
A User-friendly and Powerful R Analysis of Large-scale Datasets
10:56

A User-friendly and Powerful R Analysis of Large-scale Datasets

Published on: November 4, 2025

379
Breakfast Habits among Schoolchildren in the City of Uruguaiana, Brazil
06:48

Breakfast Habits among Schoolchildren in the City of Uruguaiana, Brazil

Published on: July 29, 2020

5.2K

Area of Science:

  • Transportation studies
  • Public transport economics
  • Consumer behavior analysis

Background:

  • Passenger satisfaction is crucial for public transport evaluation and loyalty.
  • Existing research on customer satisfaction in public transport is limited and often city-specific.
  • Cross-system comparisons of passenger satisfaction are needed.

Purpose of the Study:

  • To investigate train passengers' satisfaction with fares across five Australian capital cities.
  • To identify socio-economic and trip-specific determinants of fare satisfaction.
  • To compare fare satisfaction across different Australian urban rail systems.

Main Methods:

  • Utilized a nationwide survey and objective train fare data from Sydney, Melbourne, Brisbane, Adelaide, and Perth.
  • Employed a random parameters ordered Logit model to analyze satisfaction determinants.
  • Accounted for unobserved heterogeneity in passenger perceptions.

Main Results:

  • Key determinants include gender, city, home-to-station transport mode, concession eligibility, cost, and waiting time.
  • Female passengers reported lower satisfaction than males; bus commuters reported higher satisfaction.
  • Significant heterogeneity in satisfaction was observed regarding cost and waiting time, with intercity fare structures also influencing perceptions.

Conclusions:

  • Passenger satisfaction with train fares is influenced by a complex interplay of individual characteristics, trip details, and city-specific fare policies.
  • Findings offer valuable insights for policymakers and transport operators to enhance service and foster rider loyalty.
  • Addressing heterogeneity in satisfaction is key to developing effective public transport strategies.