Introduction to Probability by. Joseph K. Blitzstein and Jessica....pdf

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Front Cover

Dedication

Contents

Preface

Chapter 1 - Probability and counting

Chapter 2 - Conditional probability

Chapter 3 - Random variables and their distributions

Chapter 4 - Expectation

Chapter 5 - Continuous random variables

Chapter 6 - Moments

Chapter 7 - Joint distributions

Chapter 8 - Transformations

Chapter 9 - Conditional expectation

Chapter 10 - Inequalities and limit theorems

Chapter 11 - Markov chains

Chapter 12 - Markov chain Monte Carlo

Chapter 13 - Poisson processes

Appendix A - Math

Appendix B - R

Appendix C - Table of distributions

Bibliography

Back Cover

Statistics Introduction to Probability lectures, Introduction to Developed from celebrated Harvard statistics Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces. The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment. • Access online or download to your smartphone, tablet or PC/Mac • Search the full text of this and other titles you own • Make and share notes and highlights • Copy and paste text and figures for use in your own documents • Customize your view by changing font size and layout K16714 WITH VITALSOURCE® EBOOK I n t r o d u c t i o n t o P r o b a b i l i t y B i l i t z s t e n • H w a n g Texts in Statistical Science Introduction to Probability Joseph K. Blitzstein Jessica Hwang K16714_cover.indd 1 6/24/14 2:38 PM

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Introduction to Probability K16714_FM.indd 1 6/11/14 2:36 PM

CHAPMAN & HALL/CRC Texts in Statistical Science Series Series Editors Francesca Dominici, Harvard School of Public Health, USA Julian J. Faraway, University of Bath, UK Martin Tanner, Northwestern University, USA Jim Zidek, University of British Columbia, Canada Statistical Theory: A Concise Introduction F. Abramovich and Y. Ritov Practical Multivariate Analysis, Fifth Edition A. Afifi, S. May, and V.A. Clark Practical Statistics for Medical Research D.G. Altman Interpreting Data: A First Course in Statistics A.J.B. Anderson Introduction to Probability with R K. Baclawski Linear Algebra and Matrix Analysis for Statistics S. Banerjee and A. Roy Statistical Methods for SPC and TQM D. Bissell Introduction to Probability J. K. Blitzstein and J. Hwang Bayesian Methods for Data Analysis, Third Edition B.P. Carlin and T.A. Louis Second Edition R. Caulcutt The Analysis of Time Series: An Introduction, Sixth Edition C. Chatfield Introduction to Multivariate Analysis C. Chatfield and A.J. Collins Problem Solving: A Statistician’s Guide, Second Edition C. Chatfield Statistics for Technology: A Course in Applied Statistics, Third Edition C. Chatfield Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians R. Christensen, W. Johnson, A. Branscum, and T.E. Hanson Modelling Binary Data, Second Edition D. Collett Modelling Survival Data in Medical Research, Second Edition D. Collett Introduction to Statistical Methods for Clinical Trials T.D. Cook and D.L. DeMets Applied Statistics: Principles and Examples D.R. Cox and E.J. Snell Multivariate Survival Analysis and Competing Risks M. Crowder Statistical Analysis of Reliability Data M.J. Crowder, A.C. Kimber, T.J. Sweeting, and R.L. Smith An Introduction to Generalized Linear Models, Third Edition A.J. Dobson and A.G. Barnett Nonlinear Time Series: Theory, Methods, and Applications with R Examples R. Douc, E. Moulines, and D.S. Stoffer Introduction to Optimization Methods and Their Applications in Statistics B.S. Everitt Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models J.J. Faraway Linear Models with R, Second Edition J.J. Faraway A Course in Large Sample Theory T.S. Ferguson Multivariate Statistics: A Practical Approach B. Flury and H. Riedwyl Readings in Decision Analysis S. French Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition D. Gamerman and H.F. Lopes K16714_FM.indd 2 6/11/14 2:36 PM

Bayesian Data Analysis, Third Edition A. Gelman, J.B. Carlin, H.S. Stern, D.B. Dunson, A. Vehtari, and D.B. Rubin Multivariate Analysis of Variance and Repeated Measures: A Practical Approach for Behavioural Scientists D.J. Hand and C.C. Taylor Practical Data Analysis for Designed Practical Longitudinal Data Analysis D.J. Hand and M. Crowder Logistic Regression Models J.M. Hilbe Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects J.S. Hodges Statistics for Epidemiology N.P. Jewell Stochastic Processes: An Introduction, Second Edition P.W. Jones and P. Smith The Theory of Linear Models B. Jørgensen Principles of Uncertainty J.B. Kadane Graphics for Statistics and Data Analysis with R K.J. Keen Mathematical Statistics K. Knight Introduction to Multivariate Analysis: Linear and Nonlinear Modeling S. Konishi Nonparametric Methods in Statistics with SAS Applications O. Korosteleva Modeling and Analysis of Stochastic Systems, Second Edition V.G. Kulkarni Exercises and Solutions in Biostatistical Theory L.L. Kupper, B.H. Neelon, and S.M. O’Brien Exercises and Solutions in Statistical Theory L.L. Kupper, B.H. Neelon, and S.M. O’Brien Design and Analysis of Experiments with SAS J. Lawson A Course in Categorical Data Analysis T. Leonard Statistics for Accountants S. Letchford Introduction to the Theory of Statistical Inference H. Liero and S. Zwanzig Statistical Theory, Fourth Edition B.W. Lindgren Stationary Stochastic Processes: Theory and Applications G. Lindgren The BUGS Book: A Practical Introduction to Bayesian Analysis D. Lunn, C. Jackson, N. Best, A. Thomas, and D. Spiegelhalter Introduction to General and Generalized Linear Models H. Madsen and P. Thyregod Time Series Analysis H. Madsen Pólya Urn Models H. Mahmoud Randomization, Bootstrap and Monte Carlo Methods in Biology, Third Edition B.F.J. Manly Introduction to Randomized Controlled Clinical Trials, Second Edition J.N.S. Matthews Statistical Methods in Agriculture and Experimental Biology, Second Edition R. Mead, R.N. Curnow, and A.M. Hasted Statistics in Engineering: A Practical Approach A.V. Metcalfe Beyond ANOVA: Basics of Applied Statistics R.G. Miller, Jr. A Primer on Linear Models J.F. Monahan Applied Stochastic Modelling, Second Edition B.J.T. Morgan Elements of Simulation B.J.T. Morgan Probability: Methods and Measurement A. O’Hagan Introduction to Statistical Limit Theory A.M. Polansky Applied Bayesian Forecasting and Time Series Analysis A. Pole, M. West, and J. Harrison Statistics in Research and Development, Time Series: Modeling, Computation, and Inference R. Prado and M. West K16714_FM.indd 3 6/11/14 2:36 PM

Introduction to Statistical Process Control P. Qiu Sampling Methodologies with Applications P.S.R.S. Rao A First Course in Linear Model Theory N. Ravishanker and D.K. Dey Essential Statistics, Fourth Edition D.A.G. Rees Stochastic Modeling and Mathematical Statistics: A Text for Statisticians and Quantitative F.J. Samaniego Statistical Methods for Spatial Data Analysis O. Schabenberger and C.A. Gotway Bayesian Networks: With Examples in R M. Scutari and J.-B. Denis Large Sample Methods in Statistics P.K. Sen and J. da Motta Singer Decision Analysis: A Bayesian Approach J.Q. Smith Analysis of Failure and Survival Data P. J. Smith Applied Statistics: Handbook of GENSTAT Analyses E.J. Snell and H. Simpson Applied Nonparametric Statistical Methods, Fourth Edition P. Sprent and N.C. Smeeton Data Driven Statistical Methods P. Sprent Generalized Linear Mixed Models: Modern Concepts, Methods and Applications W. W. Stroup Survival Analysis Using S: Analysis of Time-to-Event Data M. Tableman and J.S. Kim Applied Categorical and Count Data Analysis W. Tang, H. He, and X.M. Tu Elementary Applications of Probability Theory, Second Edition H.C. Tuckwell Introduction to Statistical Inference and Its Applications with R M.W. Trosset Understanding Advanced Statistical Methods P.H. Westfall and K.S.S. Henning Statistical Process Control: Theory and Practice, Third Edition G.B. Wetherill and D.W. Brown Generalized Additive Models: An Introduction with R S. Wood Epidemiology: Study Design and Data Analysis, Third Edition M. Woodward Experiments B.S. Yandell K16714_FM.indd 4 6/11/14 2:36 PM

Texts in Statistical Science Introduction to Probability Joseph K. Blitzstein Harvard University Cambridge, Massachusetts, USA Jessica Hwang Stanford University Stanford, California, USA K16714_FM.indd 5 6/11/14 2:36 PM

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