Full metadata record
| DC pole | Hodnota | Jazyk |
|---|---|---|
| dc.contributor.author | Říha, David | |
| dc.contributor.author | Stros, Michael | |
| dc.date.accessioned | 2019-02-22T09:13:32Z | |
| dc.date.available | 2019-02-22T09:13:32Z | |
| dc.date.issued | 2018 | |
| dc.identifier.citation | Trendy v podnikání = Business trends : vědecký časopis Fakulty ekonomické ZČU v Plzni. 2018, č. 1, roč. 8, s. 45-55. | cs |
| dc.identifier.issn | 1805-0603 | |
| dc.identifier.uri | http://hdl.handle.net/11025/31019 | |
| dc.identifier.uri | https://drive.google.com/drive/folders/1LxJN4JSfOhOxX_FK0xL7D4baGf4iQOAn | |
| dc.format | 11 s. | cs |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en | en |
| dc.publisher | Západočeská univerzita v Plzni | cs |
| dc.relation.ispartofseries | Trendy v podnikání | cs |
| dc.rights | © Západočeská univerzita v Plzni | cs |
| dc.subject | analýza podnikových dat | cs |
| dc.subject | heterogenní datový set | cs |
| dc.subject | hierarchický lineární model | cs |
| dc.subject | vícenásobná regrese | cs |
| dc.title | Linear models based on business data from the pharmaceutical industry | en |
| dc.type | článek | cs |
| dc.type | article | en |
| dc.rights.access | openAccess | en |
| dc.type.version | publishedVersion | en |
| dc.description.abstract-translated | This article describes the analysis of heterogeneous market data. For this purpose, the most relevant methodological aspects are discussed and analyses using a hierarchical linear model and multiple regression are presented. In the first step, the applied data set is presented, and the assumed hierarchical two-level structure is shown. The data are then prepared for the analysis. The data are checked for outliers, a multicollinearity check is conducted, a new variable introduced, missing values are replaced by estimated values, a transformation procedure is conducted in order to obtain normality, the data are aggregated for each hierarchical level and a sample size test is performed. The results of both methods are discussed. Finally, it is concluded that whereas the application of a hierarchical linear model appears to be one option, a multiple regression analysis can be employed instead if the quality of the data, especially the sample size, is not sufficient. | en |
| dc.subject.translated | business data analysis | en |
| dc.subject.translated | heterogeneous data set | en |
| dc.subject.translated | hierarchical linear model | en |
| dc.subject.translated | multiple regression | en |
| dc.identifier.doi | https://doi.org/10.24132/jbt.2018.8.1.45_55 | |
| dc.type.status | Peer-reviewed | en |
| Vyskytuje se v kolekcích: | Číslo 1 (2018) Číslo 1 (2018) | |
Soubory připojené k záznamu:
| Soubor | Popis | Velikost | Formát | |
|---|---|---|---|---|
| 6_Riha_Stros.pdf | Plný text | 249,29 kB | Adobe PDF | Zobrazit/otevřít |
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