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Analysis of Using Quantitative Tools in the 57 largest German Companies listed in the Stock Exchange in 2006

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Author:Pramudita, Christoper Dewangga
Date of Publication: 2017
Book classification:Business & ManagementEnglish Books,
No. of pages:44 Pages
Format:Paperback

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Seminar paper from the year 2017 in the subject Economics - Statistics and Methods, University of Applied Sciences Brandenburg, language: English, abstract: According to Daimler Annual Report 2015 that we can find data about how many employees that Daimler AG have and whether or not the number of Daimler AGs employees gives impact on an increase or decrease of Daimler AGs revenue as well as earnings. Daimler AG involves five divisions such as Mercedes-Benz Cars, Daimler Trucks, Mercedes-Benz Vans, Daimler Buses and Daimler Financial Services. To facilitate a better comparison view between the number of employees, Earnings (EBIT) and Revenue the author decided to select the data with only arising the relevant data with his objectives. From 2013 to 2015 in department of Mercedes-Benz Cars, Mercedes-Benz Vans and Daimler Financial Services there is a correlation between an increase of the number of employees with EBIT and Revenue. Conversely, in department of Daimler Trucks and Daimler Buses with the same period looks uncorrelated between an increase of the number of employees and Revenue. In Daimler Group a correlation between the high number of employees with an increase of their share price and their market capitalization is shown where in 2012 the number of their employees about 279.972 increased about 284.015. This increase was followed by an increase of share price from 68,97 to 77,58 and of Market capitalization from 73 to 83. Because of that, in this paper we would briefly proof how strong the correlation between one factor with other factors through SPSS software which would be used to observe their correlation with aid of descriptive statistics (e.g. Histogram, Mean, Variance, Minimum, Maximum and Scatter plot) and inferential statistics (Linear Regression, Multiple Regression, Multicollinearity and Outliers) [...]
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SKU9783668441682
Manufacturer Number9783668441682
year published2017
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