Statistical inference for data science

by Brian Caffo

This book gives a brief, but rigorous, treatment of statistical inference intended for practicing Data Scientists.

Brian Caffo is a professor in the Department of Biostatistics at the Johns Hopkins University Bloomberg School of Public Health. He coleads a working group, www.smart-stats.org, that focuses on the statistical analysis of imaging and biosignals. He is the recipient of the Presidential Early Career Award for Scientists and Engineers and was named a fellow of the American Statistical Association.

117 pages, ebook

First published February 25, 2015

About the author

Brian Caffo is a professor in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. He graduated from the Department of Statistics at the University of Florida in 2001, and from the Department of Mathematics at UF in 1995. His doctoral advisor was James G. Booth. He works in the fields of computational statistics and neuroinformatics and co-created the SMART working group. He has been the recipient of the Presidential Early Career Award for Scientists and Engineers, Johns Hopkins Bloomberg School of Public Health Golden Apple and AMTRA teaching awards.

Reviews

[Ameen AboDabash · Rating 1 out of 5]

Book is a book, I don't like the idea of embedded videos, and even the videos not enough to digest the subject, I had many times to google or to find other resources to just understand simple staff, good efforts from the Auther, with all my respect but some staff explained simply elsewhere.

[Emmi · Rating 3 out of 5]

This is not much giving a better idea in a deep level of statistical inference. It is just like a handbook and it contains some practices in R. For a tutorial, it might work well, not much in the real world problems or the person who needs to get more statistical inference.

[Pooia · Rating 4 out of 5]

Very nice and concise, need to watch the related videos from Coursera as well. You might need to read it over and over to get some of the complicated concepts, but it is worth it.

[Pete · Rating 4 out of 5]

I enjoyed reading Brian Caffo's book that supports the Coursera Course on Statistical Inference. The linked video format and associated notes create a nice format to work through the materials. The book is pretty condensed though approachable, my sense would be to update to add a further reading section.

[David English · Rating 3 out of 5]

I think a lot of the reviews misunderstood the purpose of this book. It's not supposed to be a standalone work. It's supposed to supplement the lectures of the course that it goes with. In that context it does a good job.

[Charles · Rating 1 out of 5]

I gave up after finding the tenth or so math error

[Johnny · Rating 1 out of 5]

A book should not direct you at every possibility to a video you should watch first to understand the following pages.