Conditional histogram analysis of discrete questionnaire data

0574160 - ÚTIA 2024 RIV US eng C - Konferenční příspěvek (zahraniční konf.)
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]
Grant CEP: GA MŠMT 8A21009
Grant ostatní: GA TA ČR(CZ) FW06010535
Institucionální podpora: RVO:67985556
Klíčová slova: conditional histograms * discrete data * Marascuilo procedure * questionnaire analysis
Obor OECD: 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.
Trvalý link: https://hdl.handle.net/11104/0344512