03328ntm a22005177i 4500 000699041 CZ-PrVSE 20230610093205.0 m d cr n|||||||||| 230610s2023 xr fsbm 000 0 eng d NEZPRACOVANÝ IMPORT ABA006 cze ABA006 ABA006 rda Shporta, Arba ISIS:165355 dis Cluster Analysis in Marketing eng Cluster analysis in marketing / Arba Shporta 2023 ?? stran : digital, PDF soubor Vedoucí práce: Jana Cibulková Diplomová práce (Ing.)—Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky, 2023 Obsahuje bibliografii Textový (vysokoškolská kvalifikační práce) Rok obhajoby 2023 Methods of cluster analysis are statistical methods, which are being studied and applied across a wide range of fields, from biology and economics, to astrology and marketing. Hence, it is crucial for such methods to be described properly in professional literature as well as in study materials, in order for it to be used adequately. This thesis is a reaction to the book Statistics for Marketing and Customer Research, by Mario Mozzaachi, where the author presents statistical methods used in marketing. Mario Mozzaachi claims that the choice of distance does not affect the outcome of hierarchical cluster analysis. The goal of this thesis to provide an overview of statistical methods used in the field of marketing; and secondly to examine the effect of distance choice in the cluster analysis process. The first goal is achieved by providing an overview of ten statistical methods used in marketing. By describing their fundamentals and application in practice. Whereas, the second goal is full filled by demonstrating the importance of distance selection in clustering process on an illustrative example, by creating a marketing persona. For this purpose three different linkage methods in combination with seven distance/similarity measures were applied in programming language R. Clustering solutions are then evaluated and compared, while contradiction of Mario Mozzaach’s claim is demonstrated. Způsob přístupu: Internet data analysis and modeling [obor dipl. práce] diplomové práce fd132022 czenas master's theses eczenas Cluster analysis Marketing Quantitative data Qualitative data Distance measures Cibulková, Jana ISIS:129091 ths Šulc, Zdeněk vse20191023055 opn Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky kn20010709399 dgg https://insis.vse.cz/zp/82787/podrobnosti VŠKP v InSIS https://insis.vse.cz/zp/82787 Hlavní práce https://insis.vse.cz/zp/82787/posudek/vedouci Hodnocení vedoucího https://insis.vse.cz/zp/82787/posudek/oponent/78361 Oponentura https://insis.vse.cz/zp/82787/podrobnosti dc:identifier NEPOSILAT VSKP vse82787 230606 82787