Abstract
The results of our study are divided into two parts: first, the analysis of the questionnaires in this chapter and, second, the analysis of the interviews (Chap. 4).
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Notes
- 1.
Discrepancies in the number of subjects can be explained by the fact that not all questions were always answered.
- 2.
The clustering in Table 1 was generated from the free text.
- 3.
Institut für Demoskopie Allensbach (2018).
- 4.
Statistical method used for sex and age: multiple regression.
- 5.
Statistical method used: one-factor analysis of variance.
- 6.
The individual subject areas were compared with each other non-parametrically in pairs using the Wilcoxon method (here, the p-value is exemplary in comparison with natural and technical sciences).
- 7.
Statistical method used: analysis of variance.
- 8.
Statistical method used: multiple regression.
- 9.
Statistical method used: analysis of variance.
- 10.
Variance resolution: 12.2 percent.
- 11.
Statistical method used: multiple regression.
- 12.
The independent variable (UV) ‘self-activity’ was binary coded [0;1]. For the regression, ‘no self-activity’ [0] was used as the UV, resulting in a negative effect. Conversely, this is positive for ‘self-activity.’
- 13.
Statistical method used: analysis of variance.
- 14.
Statistical method used: multiple regression. The mean value is formed from the one-factor analysis of variance of the formal educational qualifications (ordinally scaled) of both parents.
- 15.
Statistical method used: multiple regression.
- 16.
Statistical method used: analysis of variance.
- 17.
The parameters ‘Art Relation’ and ‘Art Knowledge’ refer to the findings of a comprehensive museum visitor study from which, among other things, the Art Affinity Index was developed as an indicator of visitors’ affinity for art (Tschacher et al. 2015). Both the index and the two parameters are explained in the following.
- 18.
Tschacher et al. (2015).
- 19.
Statistical method used: bivariate regression.
- 20.
Here, the real observed frequencies are compared with the expected frequencies with absolute independence. Accordingly, a high Chi2 value suggests a dependency.
Bibliography
Institut für Demoskopie Allensbach. (2018). Beliebteste Musikrichtungen in Deutschland im Jahr 2018. [Top favourite music genres in Germany in 2018]. www.de.statista.com/statistik/daten/studie/171224/umfrage/beliebteste-musikrichtungen/. (Accessed 8 January 2018).
Tschacher, Wolfgang, Bergomi, Claudia, & Tröndle, Martin. (2015). The Art Affinity Index (AAI): An instrument to assess art relation and art knowledge. Empirical Studies of the Arts 33(2), 161–74.
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Tröndle, M., Weining, C., Sailer, A., Tschacher, W. (2022). (Non-)visitors in Quantitative Terms. In: Tröndle, M. (eds) Non-Visitor Research. Edition WÜRTH Chair of Cultural Production. Palgrave Macmillan, Wiesbaden. https://doi.org/10.1007/978-3-658-35181-6_3
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