ISBN
| 9781852338961 |
DDC
| 519.2 |
Tác giả CN
| Dekking, Michel |
Nhan đề
| A modern introduction to probability and statistics : understanding why and how / Michel Dekking, Cor Kraaikamp, Hendrik P Lopuhaä... |
Thông tin xuất bản
| London : Springer, 2005 |
Mô tả vật lý
| 486 p. ; |
Tóm tắt
| "A Modern Introduction to Probability and Statistics has numerous quick exercises to give direct feedback to the students. In addition the book contains over 350 exercises, half of which have answers, of which half have full solutions. The only pre-requisite for the book is a first course in calculus; the text covers standard statistics and probability material, and develops beyond traditional parametric models to the Poisson process, and on to useful modern methods such as the bootstrap." "This will be a key text for undergraduates in Computer Science, Physics, Mathematics, Chemistry, Biology and Business Studies who are studying a mathematical statistics course, and also for more intensive engineering statistics courses for undergraduates in all engineering subjects." |
Từ khóa tự do
| Probabilities |
Từ khóa tự do
| Mathematical statistics |
Từ khóa tự do
| Manuels d'enseignement supérieur. |
Khoa
| Khoa Cơ bản |
Tác giả(bs) CN
| Kraaikamp, Cornelis |
Tác giả(bs) CN
| Lopuhaä, Hendrik P |
Tác giả(bs) CN
| Meester, Erwin |
Địa chỉ
| Thư Viện Đại học Nguyễn Tất Thành |
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300 | |a486 p. ; |
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520 | |a"A Modern Introduction to Probability and Statistics has numerous quick exercises to give direct feedback to the students. In addition the book contains over 350 exercises, half of which have answers, of which half have full solutions. The only pre-requisite for the book is a first course in calculus; the text covers standard statistics and probability material, and develops beyond traditional parametric models to the Poisson process, and on to useful modern methods such as the bootstrap." "This will be a key text for undergraduates in Computer Science, Physics, Mathematics, Chemistry, Biology and Business Studies who are studying a mathematical statistics course, and also for more intensive engineering statistics courses for undergraduates in all engineering subjects." |
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