Veridical Data Science : The Practice of Responsible Data Analysis and Decision Making - Bin Yu

Instant online reading.
Don't wait for delivery!
Go digital and save!

Veridical Data Science

The Practice of Responsible Data Analysis and Decision Making

By: Bin Yu, Rebecca Barter

Write A Review

Hardcover | 15 October 2024

At a Glance

Hardcover
526 Pages

Dimensions(cm)
23.6 x 16.0 x 3.9

Hardcover

$203.75

or 4 interest-free payments of $50.94 with

Ships in 10 to 15 business days

Using real-world data case studies, this innovative and accessible textbook introduces an actionable framework for conducting trustworthy data science.

Using real-world data case studies, this innovative and accessible textbook introduces an actionable framework for conducting trustworthy data science.

Most textbooks present data science as a linear analytic process involving a set of statistical and computational techniques without accounting for the challenges intrinsic to real-world applications. Veridical Data Science, by contrast, embraces the reality that most projects begin with an ambiguous domain question and messy data; it acknowledges that datasets are mere approximations of reality while analyses are mental constructs.
Bin Yu and Rebecca Barter employ the innovative Predictability, Computability, and Stability (PCS) framework to assess the trustworthiness and relevance of data-driven results relative to three sources of uncertainty that arise throughout the data science life cycle- the human decisions and judgment calls made during data collection, cleaning, and modeling. By providing real-world data case studies, intuitive explanations of common statistical and machine learning techniques, and supplementary R and Python code, Veridical Data Science offers a clear and actionable guide for conducting responsible data science. Requiring little background knowledge, this lucid, self-contained textbook provides a solid foundation and principled framework for future study of advanced methods in machine learning, statistics, and data science.

Presents the Predictability, Computability, and Stability (PCS) methodology for producing trustworthy data-driven results
Teaches how a data science project should be conducted from beginning to end, including extensive discussion of the data scientist's decision-making process
Cultivates critical thinking throughout the entire data science life cycle
Provides practical examples and illuminating case studies of real-world data analysis problems with associated code, exercises, and solutions
Suitable for advanced undergraduate and graduate students, domain scientists, and practitioners

Shipping

	Standard Shipping	Express Shipping
Metro postcodes:	$9.99	$14.95
Regional postcodes:	$9.99	$14.95
Rural postcodes:	$9.99	$14.95

Orders over $79.00 qualify for free shipping.

How to return your order

At Booktopia, we offer hassle-free returns in accordance with our returns policy. If you wish to return an item, please get in touch with Booktopia Customer Care.

Additional postage charges may be applicable.