Quantitative research can be carried out in an unnatural, artificial environment so that a level of control can be applied to the exercise. This level of control can be achieved through laboratory experiments that allow comparing with the real world results. Also the results allow the researcher to know the variance between different dependents and independents of the study. In addition preset answers will not necessarily reflect consequences of a variable but also can elicit an entirely new outcome in some instances. This type of results can be seen in the scientific research applications.
Quantitative methods are ideally suited for finding out who, what, when, and where (Day, 1998). Quantitative methods use structured and standardized methods that allows for greater objectivity and accuracy of results. Using standards means that the research can be replicated, analyses and compared with similar studies. Usually, quantitative methods are designed to provide summaries of data that support generalization about the phenomenon under the scope of study. To accomplish this, quantitative research employs prescribed procedures to ensure validity and reliability. Kruger (2003) confirms that quantitative methods allow us to summarize vast sources of information and ease comparisons across categories and over time.
The development of standard questions by researchers can lead to structural bias and false representation, where the study actually expects the view of respondent or participating subject instead of the researcher. However, personal bias can be reduced by researchers keeping a 'distance' from participating subjects and employing subjects unknown to them.
The results of the quantitative research are limited, as they provide numerical descriptions rather than detailed narrative of the entire research perception. Additionally, these statistics yields insignificant results.
Quantitative methods only deal with issues known at the beginning of the research project as this is when the questions are decided and documented (McCullough, 1995). They can also be complex process and require considerable investment for proper understanding and using (Kruger, 2003). So, Kruger (2003) discusses how it can be difficult to get the real meaning of an issue by looking at numbers.
In Quantitative analysis, the questions have to be direct and easily quantified, and made available to a sample of no less than two hundred participants to permit reliable statistical analysis (Urban Wallace & Associates, 1995). Kruger also warns that people could tune out elaborate statistics, creating difficulties in the utilization of the products of research.
As highlighted by Honey and Mumford (1986) all learning styles have their own advantages and disadvantages and therefore no single style can be considered the best method to undertake. So the current research study adopts the usage of quantitative method of study to identify the hypothesis.
The quantitative analysis process is used to gather and compile data from the questionnaire and to analyze it so identify the factors of motivation for the European employees. The results obtained in the survey were analyzed using quantitative analysis methods. The quantitative analysis exactly interprets on how any respondents rated a certain factor at level 1 or 2 or good or bad. The data