Brace yourself for the high-octane head rush of Stateshift! The aim of Stateshift is to cunningly use a series of power-ups to boost bash drift & simply destroy your opponents as well as stay on the road ahead! Take on 15 other fearless racers across 9 exhilarating tournaments to claim your title as the greatest driver in the world! Set in the future during a period of political unrest a series of bloody conflicts have brought the world&s economy to the brink of collapse This has resulted in mass global poverty where the poor strive to survive with only one motivation illegal Stateshift racing! Danger is never far away with a full arsenal of devastating weaponry armed & ready to unleash at the touch of a button Collect homing missiles mines rocket launchers to gain the edge in a race to the finish line where only the fastest & deadliest pilots will survive Use the different abilities to shift your vehicle into 4 different states
- dragster scorch ghost & mammoth Use these " Stateshifts" to give yourself the edge & defeat the competition in this hi-speed futuristic racer Activate the impressive " Stateshifts" without releasing the gas pedal for a second Crush your friends in head-to-head multiplayer action! Obliterate your rivals using a variety of devastating weapons!
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Please note this is a region 2 DVD & will require a region 2 (Europe) or region Free DVD Player in order to play A couple facing marital problems after losing their child finds their life together further complicated by a mysterious visitor Actors Sarah Shahi Milo Ventimiglia Sara Paxton William Mapother Devon Ogden Dominic Bogart Luke Barnett John Hermann Ahmad Russ Brett Mann Oz Kalvan Preston Peterson Brody Gusar Joshua Stone & Sky Mc Mullan Director Todd Levin Certificate 15 years & over Year 2013 Screen 169 Anamorphic Languages Dolby Digital (20) Stereo Duration 1 hour & 20 minutes (approx) Region Region 2
- Will only play on European Region 2 or multi-region DVD players
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Tracklist Knots Youth Trash Fields Of Abuse Static Me Safety Lines Faster Fitting Flesh Sober Needs The Golden Guts Blister In Case Of Doubt ...

Longlisted for the Bailey's Prize 2015 The New York Times Bestseller 2014 National Book Awards Finalist 2015 PENFaulkner Award Finalist What was lost in the collapse almost everything almost everyone but there is still such beauty One snowy night in Toronto famous actor Arthur Leander dies on stage whilst performing the role of a lifetime That same evening a deadly virus touches down in North America The world will never be the same again Twenty years later Kirsten an actress in the Travelling Symphony performs Shakespeare in the settlements that have grown up since the collapse But then her newly hopeful world is threatened If civilization was lost what would you preserve? & how far would you go to protect it?'BEST NOVEL The big one One of the 2014 books that I did read stands above all the others Station Eleven by Emily St John Mandel beautifully written & wonderfully elegiac a book that I will long remember & return to' George RR Martin author of Game of Thrones' Emily St John Mandel's Station Eleven is that rare find that feels familiar & extraordinary at the same time This is truly something special' Erin Morgenstern author of The Night Circus ...

Praise for the First Edition of Statistical Analysis with Missing Data " An important contribution to the applied statistics literature I give the book high marks for unifying & making accessible much of the past & current work in this important area" William E Strawderman Rutgers University " This bookprovides interesting real-life examples stimulating end-of-chapter exercises & up-to-date references It should be on every applied statistician s bookshelf" The Statistician " The book should be studied in the statistical methods department in every statistical agency" Journal of Official Statistics Statistical analysis of data sets with missing values is a pervasive problem for which standard methods are of limited value The first edition of Statistical Analysis with Missing Data has been a standard reference on missing-data methods Now reflecting extensive developments in Bayesian methods for simulating posterior distributions this Second Edition by two acknowledged experts on the subject offers a thoroughly up-to-date reorganized survey of current methodology for handling missing-data problems Blending theory & application authors Roderick Little & Donald Rubin review historical approaches to the subject & describe rigorous yet simple methods for multivariate analysis with missing values They then provide a coherent theory for analysis of problems based on likelihoods derived from statistical models for the data & the missing-data mechanism & apply the theory to a wide range of important missing-data problems The new edition now enlarges its coverage to include Expanded coverage of Bayesian methodology both theoretical & computational & of multiple imputation Analysis of data with missing values where inferences are based on likelihoods derived from formal statistical models for the data-generating & missing-data mechanisms Applications of the approach in a variety of contexts including regression factor analysis contingency table analysis time series & sample survey inference Extensive references examples & exercises Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue Statistical Analysis With Missing Data was among those chosen ...

Statistical Concepts consists of the last 9 chapters of An Introduction to Statistical Concepts 3rd ed Designed for the second course in statistics it is one of the few texts that focuses just on intermediate statistics The book highlights how statistics work & what they mean to better prepare students to analyze their own data & interpret SPSS & research results As such it offers more coverage of non-parametric procedures used when standard assumptions are violated since these methods are more frequently encountered when working with real data Determining appropriate sample sizes is emphasized throughout Only crucial equations are included The new edition features New co-author Debbie L Hahs-Vaughn the 2007 recipient of the University of Central Florida's College of Education Excellence in Graduate Teaching Award A new chapter on logistic regression models for today's more complex methodologies Much more on computing confidence intervals & conducting power analyses using GPower All new SPSS version 19 screenshots to help navigate through the program & annotated output to assist in the interpretation of results Sections on how to write-up statistical results in APA format & new templates for writing research questions New learning tools including chapter-opening vignettes outlines a list of key concepts Stop & Think boxes & many more examples tables & figures More tables of assumptions & the effects of their violation including how to test them in SPSS 33 new conceptual computational & all new interpretative problems A website with Power Points answers to the even-numbered problems detailed solutions to the odd-numbered problems & test items for instructors & for students the chapter outlines key concepts & datasets Each chapter begins with an outline a list of key concepts & a research vignette related to the concepts Realistic examples from education & the behavioral sciences illustrate those concepts Each example examines the procedures & assumptions & provides tips for how to run SPSS & develop an APA style write-up Tables of assumptions & the effects of their violation are included along with how to test assumptions in SPSS Each chapter

Includes:: computational conceptual & interpretive problems Answers to the odd-numbered problems are provided The SPSS data sets that correspond to the book's examples & problems are available on the web The book covers basic & advanced analysis of variance models & topics not dealt with in other texts such as robust methods multiple comparison & non-parametric procedures & multiple & logistic regression models Intended for courses in intermediate statistics andor statistics II taught in education andor the behavioral sciences predominantly at the master's or doctoral level Knowledge of introductory statistics is assumed

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Discover New Methods for Dealing with High-Dimensional Data A sparse statistical model has only a small number of nonzero parameters or weights; therefore it is much easier to estimate & interpret than a dense model Statistical Learning with Sparsity The Lasso & Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data Top experts in this rapidly evolving field the authors describe the lasso for linear regression & a simple coordinate descent algorithm for its computation They discuss the application of 1 penalties to generalized linear models & support vector machines cover generalized penalties such as the elastic net & group lasso & review numerical methods for optimization They also present statistical inference methods for fitted (lasso) models including the bootstrap Bayesian methods & recently developed approaches In addition the book examines matrix decomposition sparse multivariate analysis graphical models & compressed sensing It concludes with a survey of theoretical results for the lasso In this age of big data the number of features measured on a person or object can be large & might be larger than the number of observations This book shows how the sparsity assumption allows us to tackle these problems & extract useful & reproducible patterns from big datasets Data analysts computer scientists & theorists will appreciate this thorough & up-to-date treatment of sparse statistical modeling ...

In each generation scientists must redefine their fields abstracting simplifying & distilling the previous standard topics to make room for new advances & methods Sethna's book takes this step for statistical mechanics
- a field rooted in physics & chemistry whose ideas & methods are now central to information theory complexity & modern biology Aimed at advanced undergraduates & early graduate students in all of these fields Sethna limits his main presentation to the topics that future mathematicians & biologists as well as physicists & chemists will find fascinating & central to their work The amazing breadth of the field is reflected in the author's large supply of carefully crafted exercises each an introduction to a whole field of study everything from chaos through information theory to life at the end of the universe
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How do beginning students of statistics for geography learn to fully understand the key concepts & apply the principal techniques? This text now in its Fourth Edition provides exactly that resource Accessibly written & focussed on student learning it's a statistics 101 that

Includes:: definitions examples & exercise throughout Now fully integrated with online self-assessment exercises & video navigation it explains everything required to get full credits for any undergraduate statistics module Descriptive statistics probability inferential statistics hypothesis testing & sampling variance correlation regression analysis spatial patterns spatial data reduction using factor analysis & cluster analysis Exercises in the text are complemented with online exercise & prompts that test the understanding of concepts & techniques additional online exercises review understanding of the entire chapter relating concepts & techniques Completely revised & updated for accessibility including new material (on measures of distance statistical power sample size selection & basic probability) with related exercises & downloadable datasets It is the only text required for undergraduate modules in statistical analysis statistical methods & quantitative geography

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Designing algorithms to recommend items such as news articles & movies to users is a challenging task in numerous web applications The crux of the problem is to rank items based on users' responses to different items to optimize for multiple objectives Major technical challenges are high dimensional prediction with sparse data & constructing high dimensional sequential designs to collect data for user modeling & system design This comprehensive treatment of the statistical issues that arise in recommender systems

Includes:: detailed in-depth discussions of current state-of-the-art methods such as adaptive sequential designs (multi-armed bandit methods) bilinear random-effects models (matrix factorization) & scalable model fitting using modern computing paradigms like Map Reduce The authors draw upon their vast experience working with such large-scale systems at Yahoo! & Linked In & bridge the gap between theory & practice by illustrating complex concepts with examples from applications they are directly involved with

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