Modern Mathematical Statistics with Applications, Second Edition
strikes a balance between mathematical foundations and statistical
practice. In keeping with the recommendation that every math student
should study statistics and probability with an emphasis on data
analysis, accomplished authors Jay Devore and Kenneth Berk make
statistical concepts and methods clear and relevant through careful
explanations and a broad range of applications involving real data.
The main focus of the book is on presenting and illustrating methods of
inferential statistics that are useful in research. It begins with a
chapter on descriptive statistics that immediately exposes the reader to
real data. The next six chapters develop the probability material that
bridges the gap between descriptive and inferential statistics. Point
estimation, inferences based on statistical intervals, and hypothesis
testing are then introduced in the next three chapters. The remainder of
the book explores the use of this methodology in a variety of more
complex settings.
This edition includes a plethora of new exercises, a number of which are
similar to what would be encountered on the actuarial exams that cover
probability and statistics. Representative applications include
investigating whether the average tip percentage in a particular
restaurant exceeds the standard 15%, considering whether the flavor and
aroma of Champagne are affected by bottle temperature or type of pour,
modeling the relationship between college graduation rate and average
SAT score, and assessing the likelihood of O-ring failure in space
shuttle launches as related to launch temperature.