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 is not to focus on the mathematical/theoretical aspects of the subject, but rather to provide an introduction to the subject tailored to the mindset and tastes of Mathematics students, who are sometimes turned off by the informal nature of Statistics courses. This book can be used as the basis for an elementary semester-long first course on Statistics with a firm sense of direction that does not sacrifice rigor. The deeper goal of the text is to attract the attention of promising Mathematics students.
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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.
The author aims to present a few topics that he considers important, striking an excellent balance between the need to be concise and to include all of the fundamental methods. & this is a valuable book for both mathematics students and applies researchers, and fills a gap in the literature by providing a rigorous and modern introduction to the basic theory of statistics. (Marco Bee, Mathematical Reviews, February, 2017)
Panaretos & provides a logical, thorough mathematical representation for a minimally selected number of topics in one-parameter statistical inference. & textbook is appropriate for those students, regardless of their disciplines, interested in learning about or becoming more familiarized with the essencel3
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