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Subjectivity statement dissertation

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Added: 15.05.2021
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Applying data analytics in production test has become a widely adopted industrial practice in recent years. As the complexity of semiconductor devices scales and the amounts of available test data continue to grow, the research direction in this field is forced to shift away from solving specific problems with ad hoc approaches and demands for deeper understanding of the fundamental issues. Two data-driven test applications where this shift is apparent are production yield optimization and defect screening, where the respective underlying data analytics approaches are correlation analysis and outlier analysis. A core issue present in these two approaches stems from the subjectivity that is inherent to data analytics. This dissertation delves into how subjectivity manifests itself and what can be done to reduce it with respect to the two test applications.
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Shivanee Shah. Qualitative research is an exploratory scientific method of observation to gather non-numerical data. Some of the common approaches to conducting qualitative research include interviews, participant observation, and focus group discussions. Often, this approach is widely used in the political science, education, and social work fields and may also be applied to market research, business, and journalism. Although scientific or academic research needs to be handled objectively, the subjective nature of qualitative research may make it difficult for the researcher to be detached completely from the data, which in other words means that it is difficult to maintain objectivity and avoid bias. As a result, qualitative research is often criticized for lacking transparency and scientific rigour. It is censured for being a compilation of impressions that are subjected to researcher bias and that may not necessarily be reproducible.
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Subjective vs. Objective

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Purposive sampling, also known as judgmental , selective or subjective sampling, is a type of non-probability sampling technique. Non-probability sampling focuses on sampling techniques where the units that are investigated are based on the judgement of the researcher [see our articles: Non-probability sampling to learn more about non-probability sampling, and Sampling: The basics , for an introduction to terms such as units , cases and sampling ]. There are a number of different types of purposive sampling, each with different goals.
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