In This Chapter
Introducing the core basics of statistical probability
Diving into about linear regression
Moving on to Monte Carlo simulations
Talking about time series analysis
Statistical methods are not the big and scary things many people try to make them out to be. In data science, the need for statistical methods is simply a fact of life, but it’s nothing to get too alarmed over. Although you have to get a handle on as much statistics as you need to solve the problem at hand, you don’t need to go out and get a degree in the field.
Contrary to what many pure statisticians would have you believe, the data science field is not the same thing as the statistics field. A data scientist is someone who has substantive knowledge of one or several fields and uses statistics, math, coding, and strong communication skills to help her tease out, understand, and communicate data insights that lie within raw datasets related to her field of expertise. Statistics is a vital component of this formula, but not more vital than the others. In ...