Methods and Challenges in Data Collection

1705 Words Apr 24th, 2013 7 Pages
Authors as Adams, Khan, Hafiz and Raeside (1), suggest some method for data collection, basing on the situation, warning from possible threats to the validity and reliability of data collected.
Whatever the method of data collection chosen (observations, experimentation, survey, interviews, diary method, case study, data storage, triangulation), there are several hypothesis that need to be considered since the beginning (1); the challenges born from the nature of the research and level of detail the researcher want to reach, then by time and budget available, so careful consideration and planning of data collection is required.
There are some common principles, for examples try to eliminate as much as possible human errors,
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Some methods for avoiding this issues, will be analyzed in the next chapter “strategies”

3.2 Characteristics of collected data
The target of the researcher is to get the data as objective as possible and the best response rate, not only in terms of numbers but as much representative as possible (2).
It means that collects objective data, makes it stronger and unassailable the research, and open to any new research or alternative solutions. Some examples of objective criteria could be: * Market value * Scientific findings * Efficiency of the model * Professional standards defined * Equal treatment * Tradition * Legal (court) * Reasonableness
Collecting the right data, allows the researcher to get representative answers which help to find a solution to the problem that he / she places, otherwise the study can be compromise since the beginning, or can drive the researcher to solution not representative of reality.
For example, company can decide to capture data of saving from a certain database characterized by having certain accuracy, i.e. two decimal places; at the end of analysis, the researcher have to know that the result is affected by a certain error value. Infact, even if minimal error is occasionally acceptable, in some cases can lead to unacceptable inaccuracy or even to the failure of the project.
For this, determine the level of tolerated

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