Introduction to the Theory of Statistical Inference

Based on the authors’ lecture notes, this text presents concise yet complete coverage of statistical inference theory, focusing on the fundamental classical principles. Unlike related textbooks, it combines the theoretical basis of statistical inference with a useful applied toolbox that includes linear models. Suitable for a second semester undergraduate course on statistical inference, the text offers proofs to support the mathematics and does not require any use of measure theory. It illustrates core concepts using cartoons and provides solutions to all examples and problems.

Hannelore Liero is an apl. Prof. for Mathematical Statistics at the University of Potsdam. She studied Mathematics at the Humboldt-University in Berlin. She earned her Ph.D. while working as a scientist at the Academy of Sciences of the GDR. Since 1992, she has taught Statistics for undergraduate and graduate students in Mathematics, Biology and Computer Science at the Faculty of Sciences at the University of Potsdam. In addition to teaching, she does basic research in Statistics and supports scientists applying statistical methods in practice.

Silvelyn Zwanzig is an Associate Professor for Mathematical Statistics at Uppsala University. She studied Mathematics at the Humboldt-University in Berlin. Before coming to Sweden she was Assistant Professor at the University of Hamburg in Germany. She received her Ph.D. in Mathematics at the Academy of Sciences of the GDR. Since 1991, she has taught Statistics for undergraduate and graduate students. Her research interests have moved from theoretical statistics to computer intensive statistics. She is interested in consulting and was working in Astrometry.