Data scientist is the hot job title du jour. Many books and sites teach the mechanics of how to make data visualizations, but skip or gloss over the foundations of data science. This talk will help you think through fundamental considerations before you plunge into your data analysis.
Can this problem be answered with data? What type of data can help me answer this question? Where can I find the best data for the job? Does the data match the data documentation? How do I cite the data for reproducibility?
Grace Peng works in the Data Support Section.
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Peng_SEA2016.notesview.pdf | 4.63 MB |