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) |
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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
- Mathematics(all)
- Statistics, Probability and Uncertainty