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Conditional histogram analysis of discrete questionnaire data
- 1.0574160 - ÚTIA 2024 RIV US eng C - Conference Paper (international conference)
Reznychenko, T. - Uglickich, Evženie - Nagy, Ivan
Conditional histogram analysis of discrete questionnaire data.
2023 Smart City Symposium Prague (SCSP). Red Hook: Curran Associates, 2023, s. 1-6. ISBN 979-8-3503-2162-3. ISSN 2831-5618. E-ISSN 2691-3666.
[Smart City Symposium Prague 2023 (SCSP 2023). Prague (CZ), 25.05.2023-26.05.2023]
R&D Projects: GA MŠMT 8A21009
Grant - others:GA TA ČR(CZ) FW06010535
Institutional support: RVO:67985556
Keywords : conditional histograms * discrete data * Marascuilo procedure * questionnaire analysis
OECD category: Statistics and probability
http://library.utia.cas.cz/separaty/2023/ZS/uglickich-0574160.pdf
The paper deals with the analysis of histograms of discrete data collected in questionnaires obtained for individual realizations of the target variable. The main aim of the analysis is to explore the influence of combinations of explanatory variables, represented by responses to the questionnaire, on the behavior
of the target variable of the questionnaire. In this paper, an automated approach to histogram comparison is proposed based on coding combinations of data and detecting significant differences in frequencies using the Marascuilo procedure. This is the main contribution of the paper. The approach is validated using a simulated questionnaire in which respondents answered regarding their intention to purchase an electric vehicle subject to finance, leasing, and charging availability, as well as their driving style. The results of the experiments are demonstrated.
Permanent Link: https://hdl.handle.net/11104/0344512
Number of the records: 1