Abstract
Graduate-level instruction in statistical computing need not be relegated to courses devoted to statistical computing; even theoretical statistics courses can include considerable computational content through well-designed exercises. Such exercises should be chosen so that they force students to learn essential computing skills without impeding instruction of theory. A series of examples used in a course on large-sample theory illustrates this thesis.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 327-333 |
| Number of pages | 7 |
| Journal | American Statistician |
| Volume | 59 |
| Issue number | 4 |
| DOIs | |
| State | Published - Nov 2005 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- General Mathematics
- Statistics, Probability and Uncertainty