Methods
In Data Science, methods refer to the techniques and procedures used to analyze and interpret data. These methods can be broadly categorized into two types: quantitative and qualitative. Quantitative methods involve the use of statistical and mathematical models to analyze numerical data, while qualitative methods involve the analysis of non-numerical data such as text, images, and videos. Some common quantitative methods used in Data Science include regression analysis, hypothesis testing, and machine learning algorithms, while common qualitative methods include content analysis, discourse analysis, and ethnography. The choice of method depends on the research question, the type of data, and the level of analysis required. A good Data Scientist should have a strong understanding of both quantitative and qualitative methods and be able to select the appropriate method for a given research question.
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