November 2017
Beginner
286 pages
8h 13m
English
book
Statistics for Data Science
by James C. Mott, Rajprasath Subramanian, Shaikh Salamatullah, James D. Miller, Vijayakumar Ramdoss
Content preview from Statistics for Data Science
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Summary
In this chapter, we explored the purpose and process of statistical analysis in detail (the differences in data analysis), created a summarization model, and listed the steps involved in a successful statistical analysis. Finally, we underscored the choice of using R as the statistical analysis tool of choice.
The next chapter will be targeted at explaining statistical regression and why it is important to data science. We will walk through the use of various statistical regression methods in everyday data projects and outline how a developer might use regression for simple forecasting and prediction within a typical data development project.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.