Difference between “computational statistics” and “statistical computing”?

Question

From Handbook of computational Statistics by Gentle et al,

We use the term “statistical computing” to refer to the computational methods that enable statistical methods. Statistical computing includes numerical analysis, database methodology, computer graphics, software engineering, and the computer/human interface.

We use the term “computational statistics” somewhat more broadly to include not only the methods of statistical computing, but also statistical methods that are computationally intensive.

Thus, to some extent, “computational statistics” refers to a large class of modern statistical methods. Computational statistics is grounded in mathematical statistics, statistical computing, and applied statistics.

So it looks like "computational statistics" is a superset of "statistical computing"?

In "computational statistics", what are the difference between "the methods of statistical computing" and "statistical methods that are computationally intensive"?

How do you understand the relation and difference between "computational statistics" and "statistical computing"?

Answer 1

Roughly speaking, Computational Statistics refers to the statistical topics that require heavy computation, while Statistical Computing refers to the computational/numerical methods that can be applied to statistics.

We apply the computational methods from Statistical Computing to implement the statistical methods from Computational Statistics.

However, the computational methods from Statistical Computing can be applied to all of Statistics (not just Computational Statistics).

Statistical Computing and Computational Statistics overlap but neither discipline is a subset of the other.