<p>This textbook provides a coherent introduction to the main concepts and methods of one-parameter statistical inference. Intended for students of Mathematics taking their first course in Statistics, the focus is on Statistics for Mathematicians rather than on Mathematical Statistics.Β The goal is n
Statistics for Mathematicians: a Rigorous First Course
β Scribed by Panaretos, Victor M
- Publisher
- Springer International Publishing
- Year
- 2016
- Tongue
- English
- Leaves
- 190
- Series
- Compact Textbooks in Mathematics
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
Foreword.- Regular Probability Models.- Sampling From Probability Distributions.- Point Estimation of Model Parameters.- Tests of Hypotheses for Model Parameters.- Confidence Intervals for Model Parameters.- Appendix.- Bibliography.
β¦ Subjects
Probabilities;Probability Theory and Stochastic Processes;Statistical Theory and Methods;Statistics;Statistics for Business/Economics/Mathematical Finance/Insurance;Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
π SIMILAR VOLUMES
<p><p>This textbook provides a coherent introduction to the main concepts and methods of one-parameter statistical inference. Intended for students of Mathematics taking their first course in Statistics, the focus is on Statistics for Mathematicians rather than on Mathematical Statistics. The goal i
<span>Designed for undergraduate mathematics majors, this rigorous and rewarding treatment covers the usual topics of first-year calculus: limits, derivatives, integrals, and infinite series. Author Daniel J. Velleman focuses on calculus asΒ a tool for problem solving rather than the subject's theore
Designed for undergraduate mathematics majors, this rigorous and rewarding treatment covers the usual topics of first-year calculus: limits, derivatives, integrals, and infinite series. Author Daniel J. Velleman focuses on calculus asΒ a tool for problem solving rather than the subject's theoretical
This text serves as an excellent introduction to statistics for signal analysis. Be aware that it emphasizes theory over numerical methods - and that it is dense. If one is not looking for lengthy explanations but instead wants to get to the point quickly this book may be for them.