|
Showing 1 - 8 of
8 matches in All Departments
This book describes methods for designing and analyzing experiments
that are conducted using a computer code, a computer experiment,
and, when possible, a physical experiment. Computer experiments
continue to increase in popularity as surrogates for and adjuncts
to physical experiments. Since the publication of the first
edition, there have been many methodological advances and software
developments to implement these new methodologies. The computer
experiments literature has emphasized the construction of
algorithms for various data analysis tasks (design construction,
prediction, sensitivity analysis, calibration among others), and
the development of web-based repositories of designs for immediate
application. While it is written at a level that is accessible to
readers with Masters-level training in Statistics, the book is
written in sufficient detail to be useful for practitioners and
researchers. New to this revised and expanded edition: * An
expanded presentation of basic material on computer experiments and
Gaussian processes with additional simulations and examples * A new
comparison of plug-in prediction methodologies for real-valued
simulator output * An enlarged discussion of space-filling designs
including Latin Hypercube designs (LHDs), near-orthogonal designs,
and nonrectangular regions * A chapter length description of
process-based designs for optimization, to improve good overall
fit, quantile estimation, and Pareto optimization * A new chapter
describing graphical and numerical sensitivity analysis tools *
Substantial new material on calibration-based prediction and
inference for calibration parameters * Lists of software that can
be used to fit models discussed in the book to aid practitioners
Now available with Macmillan's new online learning tool Achieve,
the ninth edition of The Basic Practice of Statistics 9e teaches
statistical thinking by guiding students through an investigative
process of problem-solving with pedagogy designed to help students
of all levels. Examples and exercises from a wide variety of topic
areas use current, real data to provide students insight into how
and why statistics are used to make decisions in the real world.
Achieve for The Basic Practice of Statistics connects the trusted
Four-Step problem-solving approach and real world examples in the
book to rich digital resources that foster further understanding
and application of statistics. Assets in Achieve support learning
before, during, and after class for students, while providing
instructors with class performance analytics in an easy-to-use
interface. Achieve Online Homework Macmillan's new online learning
tool Achieve features intuitive design, assessment, insights, and
reporting built with the direct input of students, educators, and
our learning science team. Achieve for The Basic Practice of
Statistics features: Learning Objectives tagged to all assessments
within Achieve. In-Class Activity Guides to facilitate active
learning during class time. over 3,000 homework questions, each
with hints, answer-specific feedback, and a fully worked solution.
LearningCurve adaptive quizzing. an interactive e-book, powered by
VitalSource. multimedia student resources, such as interactive
applets and videos. data sets for common statistical software,
video technology manuals, and access to Macmillan's proprietary
statistical software, CrunchIt! Content Updates to the Ninth
Edition: Examples and exercises more clearly emphasize the
decision-making process. Chapter Summaries and Review Chapters have
been revised to help students check their knowledge and review for
exams. - Summaries are in concise list form, and Skills Reviews (in
Review Chapters) refer back to relevant chapter sections. Data in
examples and exercises have been updated for currency, and new
examples and exercises explore contemporary issues such as social
media usage.
This practical textbook by David Moore and William Notz introduces
a conceptual approach to statistics and shows students how use
these ideas to think about the statistical claims they see every
day from polls, campaigns, advertising, public policy, and many
different fields of study. The ultimate goal is to equip students
with solid statistical reasoning skills that will help them
understand impact of statistics on all aspects of their lives.
This 1998 book describes the sampling and statistical methods used
most often by behavioral ecologists and field biologists. Written
by a biologist and two statisticians, it provides a rigorous
discussion together with worked examples of statistical concepts
and methods that are generally not covered in introductory courses,
and which are consequently poorly understood and applied by field
biologists. The first section reviews important issues such as
defining the statistical population and the sampling plan when
using non-random methods for sample selection, bias, interpretation
of statistical tests, confidence intervals and multiple
comparisons. After a detailed discussion of sampling methods and
multiple regression, subsequent chapters discuss specialized
problems such as pseudoreplication, and their solutions. It will
quickly become the statistical handbook for all field biologists.
This book describes methods for designing and analyzing
experiments conducted using computer code in lieu of a physical
experiment. It discusses how to select the values of the factors at
which to run the code (the design of the computer experiment). It
also provides techniques for analyzing the resulting data so as to
achieve these research goals.
This book describes the sampling and statistical methods used most often by behavioral ecologists and field biologists. Written by a biologist and two statisticians, it provides a rigorous discussion together with worked examples of statistical concepts and methods that are generally not covered in introductory courses, and which are consequently poorly understood and applied by field biologists. The first section reviews important issues such as defining the statistical population and the sampling plan when using nonrandom methods for sample selection, bias, interpretation of statistical tests, confidence intervals, and multiple comparisons. After a detailed discussion of sampling methods and multiple regression, subsequent chapters discuss specialized problems such as pseudoreplication, and their solutions. This volume will quickly become the favorite statistical handbook for all field biologists.
This volume reveals the applications of statistics to a wide range
of fields, from public policy to the sciences. It introduces new
technology and pedagogical features.
|
|