Statistics for Data Science
by James C. Mott, Rajprasath Subramanian, Shaikh Salamatullah, James D. Miller, Vijayakumar Ramdoss
Causes of bias
Bias is a term that you will find is commonly thrown around in the field of statistics and, almost always, bias is equivalent to (or with) a negative or bad incident. In fact, even beyond the realm of statistics, bias almost always results in trouble or some form of distress.
Consider bias as favoritism. Favoritism that is present in the data collection process, for example, will typically result in misleading results or incorrect assumptions.
Bias can arise in various ways and, as a data scientist, one must be familiar with these occasions. Actually, bias can be introduced to a statistical project at any time or phase.
One of the most common times that bias is introduced is at the very start or beginning of a project when ...
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