Content
October 2020, Volume 75, Issue 2
- 217-225 The Lorenz Curve in the Classroom
by Roberta La Haye & Petr Zizler
October 2020, Volume 75, Issue 1
December 2020, Volume 75, Issue 1
October 2020, Volume 74, Issue 4
- 317-328 A Time-Series Model for Underdispersed or Overdispersed Counts
by Iain L. MacDonald & Feroz Bhamani - 329-344 Big Data? Statistical Process Control Can Help!
by Peihua Qiu - 345-358 Applications of the Fractional-Random-Weight Bootstrap
by Li Xu & Chris Gotwalt & Yili Hong & Caleb B. King & William Q. Meeker - 359-369 Assessing Bayes Factor Surfaces Using Interactive Visualization and Computer Surrogate Modeling
by Christopher T. Franck & Robert B. Gramacy - 370-379 Decision-Theoretic Hypothesis Testing: A Primer With R Package OptSig
by Jae H. Kim - 380-391 Going Viral, Binge-Watching, and Attention Cannibalism
by Scott D. Grimshaw & Natalie J. Blades & Candace Berrett - 392-406 Random Forest Prediction Intervals
by Haozhe Zhang & Joshua Zimmerman & Dan Nettleton & Daniel J. Nordman - 407-412 Gaussian Mixture Representation of the Laplace Distribution Revisited: Bibliographical Connections and Extensions
by Tomasz J. Kozubowski & Krzysztof Podgórski - 413-415 Revisiting Jeffreys’ Example: Bayes Test of the Normal Mean
by Malay Ghosh - 416-417 Mathematical and Statistical Skills in the Biopharmaceutical Industry: A Pragmatic Approach
by Wen Li & Thomas O. Jemielita - 417-417 Multiple Imputation in Practice: With Examples Using IVEware
by Qixuan Chen - 418-418 Xinjie Hu, Aekyung Jung, and Gengsheng Qin (2020), “Interval Estimation for the Correlation Coefficient,” The American Statistician, 74:1, 29–36: Comment by Krishnamoorthy and Xia
by Kalimuthu Krishnamoorthy & Yanping Xia - 419-419 A Response to the Letter to the Editor on “Interval Estimation for the Correlation Coefficient,” The American Statistician, 74:1, 29–36: Comment by Krishnamoorthy and Xia
by Xinjie Hu & Aekyung Jung & Gengsheng Qin - 420-421 Editorial Collaborators
by The Editors
July 2020, Volume 74, Issue 3
- 213-217 The Detection of Nonnegligible Directional Effects With Associated Measures of Statistical Significance
by Melinda H. McCann & Joshua D. Habiger - 218-225 Some Improvements on Markov's Theorem with Extensions
by Haruhiko Ogasawara - 226-232 Compound Regression and Constrained Regression: Nonparametric Regression Frameworks for EIV Models
by Ling Leng & Wei Zhu - 233-242 Nonparametric Estimation of the Conditional Distribution at Regression Boundary Points
by Srinjoy Das & Dimitris N. Politis - 243-248 On Causal Inferences for Personalized Medicine: How Hidden Causal Assumptions Led to Erroneous Causal Claims About the D-Value
by Sander Greenland & Michael P. Fay & Erica H. Brittain & Joanna H. Shih & Dean A. Follmann & Erin E. Gabriel & James M. Robins - 249-257 Bayesian Causality
by Pierre Baldi & Babak Shahbaba - 258-266 Detecting Directionality in Time Series
by Mahayaudin M. Mansor & David A. Green & Andrew V. Metcalfe - 267-273 Bias in Small-Sample Inference With Count-Data Models
by McKinley L. Blackburn - 274-281 A New Analysis Strategy for Designs With Complex Aliasing
by Andrew Kane & Abhyuday Mandal - 282-293 Trend and Return Level of Extreme Snow Events in New York City
by Mintaek Lee & Jaechoul Lee - 294-296 On a Proper Bayes, but Inadmissible Estimator
by Pankaj Bhagwat & Éric Marchand - 297-300 On the Maximum–Minimums Identity: Extension and Applications
by Ibrahim Salama & Gary Koch - 301-306 Was Quetelet’s Average Man Normal?
by Eugene D. Gallagher - 307-307 The 9 Pitfalls of Data Science
by Yongdai Kim - 308-309 Feature Engineering and Selection: A Practical Approach for Predictive Models
by Brandon Butcher & Brian J. Smith - 309-311 Modern Statistics for Modern Biology
by Bailey K. Fosdick & G. Brooke Anderson - 311-311 Surprises in Probability: Seventeen Short Stories
by Jonathan M. Wells - 312-312 Time Series: A Data Analysis Approach Using R
by Robert B. Lund - 313-314 Comment on “Test for Trend With a Multinomial Outcome” by Szabo (2019)
by Ronald Christensen - 315-315 Micha Mandel (2020), “The Scaled Uniform Model Revisited,” The American Statistician, 74:1, 98–100: Comment
by Gunnar Taraldsen
April 2020, Volume 74, Issue 2
- 103-108 Where Should I Publish My Sports Paper?
by Tim B. Swartz - 109-115 Wilson Confidence Intervals for Binomial Proportions With Multiple Imputation for Missing Data
by Anne Lott & Jerome P. Reiter - 116-124 The Relative Performance Index: Neutralizing Simpson's Paradox
by Ernest C. Davenport, & Kyle Nickodem & Mark L. Davison & Gareth Phillips & Edmund Graham - 125-136 Iterative Multiple Imputation: A Framework to Determine the Number of Imputed Datasets
by Vahid Nassiri & Geert Molenberghs & Geert Verbeke & João Barbosa-Breda - 137-143 Informed Bayesian t-Tests
by Quentin F. Gronau & Alexander Ly & Eric-Jan Wagenmakers - 144-155 Visualizing Tests for Equality of Covariance Matrices
by Michael Friendly & Matthew Sigal - 156-168 Plotting Likelihood-Ratio-Based Confidence Regions for Two-Parameter Univariate Probability Models
by Christopher Weld & Andrew Loh & Lawrence Leemis - 169-183 Archetypal Analysis With Missing Data: See All Samples by Looking at a Few Based on Extreme Profiles
by Irene Epifanio & M. Victoria Ibáñez & Amelia Simó - 184-189 Time Parameterizations in Cluster Randomized Trial Planning
by Kelsey L. Grantham & Andrew B. Forbes & Stephane Heritier & Jessica Kasza - 190-196 How Does a Statistician Raise an Army? The Time When John W. Tukey, a Team of Luminaries, and a Statistics Graduate Student Repaired the Vietnam Selective Service Lotteries
by Tim Johnson & Christopher T. Dawes & Dalton Conley - 197-206 Lest We Forget: U.S. Selective Service Lotteries, 1917–2019
by James A. Hanley - 207-207 The Art of Statistics: How to Learn From Data
by Jong Hee Park - 207-208 Capture-Recapture Methods for the Social and Medical Sciences
by Daniel Manrique-Vallier - 208-209 Model-Based Clustering and Classification for Data Science: With Applications in R
by Seung Jun Shin - 209-210 R Markdown: The Definitive Guide
by Paul Johnson - 211-211 Did Phlegon Actually Use a Stem-and-Leaf Display?
by David C. Hoaglin - 212-212 Correction
by The Editors
January 2020, Volume 74, Issue 1
- 1-7 The Democratization of Data Science Education
by Sean Kross & Roger D. Peng & Brian S. Caffo & Ira Gooding & Jeffrey T. Leek - 8-16 Fostering Undergraduate Data Science
by Fulya Gokalp Yavuz & Mark Daniel Ward - 17-20 A Short Note on Almost Sure Convergence of Bayes Factors in the General Set-Up
by Debashis Chatterjee & Trisha Maitra & Sourabh Bhattacharya - 21-28 Generating Correlation Matrices With Specified Eigenvalues Using the Method of Alternating Projections
by Niels G. Waller - 29-36 Interval Estimation for the Correlation Coefficient
by Xinjie Hu & Aekyung Jung & Gengsheng Qin - 37-52 The Johnson System of Frequency Curves—Historical, Graphical, and Limiting Perspectives
by Johan René van Dorp & M. C. Jones - 53-63 A Note on Item Response Theory Modeling for Online Customer Ratings
by Chien-Lang Su & Sun-Hao Chang & Ruby Chiu-Hsing Weng - 64-67 On the Loss Robustness of Least-Square Estimators
by Tamal Ghosh & Malay Ghosh & Tatsuya Kubokawa - 68-71 Comment on “A Note on Collinearity Diagnostics and Centering” by Velilla (2018)
by Román Salmerón Gómez & Catalina García García & Jose García Pérez - 72-79 Models for Geostatistical Binary Data: Properties and Connections
by Victor De Oliveira - 80-86 Two-Tailed p-Values and Coherent Measures of Evidence
by Peter H. Peskun - 87-92 A Shiny Update to an Old Experiment Game
by Robert B. Gramacy - 93-97 Further Examples Related to the Identical Distribution of X/(X+Y) and Y/(X+Y)
by Barry C. Arnold - 98-100 The Scaled Uniform Model Revisited
by Micha Mandel - 101-102 Benjamin, D. J., and Berger, J. O. (2019), “Three Recommendations for Improving the Use of p-Values”, The American Statistician, 73, 186–191: Comment by Foulley
by Jean-Louis Foulley
March 2019, Volume 73, Issue S1
- 1-19 Moving to a World Beyond “p
by Ronald L. Wasserstein & Allen L. Schirm & Nicole A. Lazar - 20-25 What Have We (Not) Learnt from Millions of Scientific Papers with P Values?
by John P. A. Ioannidis - 26-30 Why is Getting Rid of P-Values So Hard? Musings on Science and Statistics
by Steven N. Goodman - 31-35 Will the ASA's Efforts to Improve Statistical Practice be Successful? Some Evidence to the Contrary
by Raymond Hubbard - 36-45 Correcting Corrupt Research: Recommendations for the Profession to Stop Misuse of p-Values
by John L. Kmetz - 46-55 Quality Control for Scientific Research: Addressing Reproducibility, Responsiveness, and Relevance
by Douglas W. Hubbard & Alicia L. Carriquiry - 56-68 The Role of Expert Judgment in Statistical Inference and Evidence-Based Decision-Making
by Naomi C. Brownstein & Thomas A. Louis & Anthony O’Hagan & Jane Pendergast - 69-81 Expert Knowledge Elicitation: Subjective but Scientific
by Anthony O’Hagan - 82-90 Before p
by Lee Kennedy-Shaffer - 91-98 The Limited Role of Formal Statistical Inference in Scientific Inference
by Raymond Hubbard & Brian D. Haig & Rahul A. Parsa - 99-105 Large-Scale Replication Projects in Contemporary Psychological Research
by Blakeley B. McShane & Jennifer L. Tackett & Ulf Böckenholt & Andrew Gelman - 106-114 Valid P-Values Behave Exactly as They Should: Some Misleading Criticisms of P-Values and Their Resolution With S-Values
by Sander Greenland - 115-117 The p-Value Requires Context, Not a Threshold
by Rebecca A. Betensky - 118-121 Assessing Statistical Results: Magnitude, Precision, and Model Uncertainty
by Andrew A. Anderson - 122-128 Putting the P-Value in its Place
by Joachim I. Krueger & Patrick R. Heck - 129-134 Evidence From Marginally Significant t Statistics
by Valen E. Johnson - 135-147 The p-value Function and Statistical Inference
by D. A. S. Fraser - 148-151 p-Values, Bayes Factors, and Sufficiency
by Jonathan Rougier - 152-156 Limitations of P-Values and R-squared for Stepwise Regression Building: A Fairness Demonstration in Health Policy Risk Adjustment
by Sherri Rose & Thomas G. McGuire - 157-167 An Introduction to Second-Generation p-Values
by Jeffrey D. Blume & Robert A. Greevy & Valerie F. Welty & Jeffrey R. Smith & William D. Dupont - 168-185 A Proposed Hybrid Effect Size Plus p-Value Criterion: Empirical Evidence Supporting its Use
by William M. Goodman & Susan E. Spruill & Eugene Komaroff - 186-191 Three Recommendations for Improving the Use of p-Values
by Daniel J. Benjamin & James O. Berger - 192-201 The False Positive Risk: A Proposal Concerning What to Do About p-Values
by David Colquhoun - 202-212 Moving Towards the Post p
by Robert A. J. Matthews - 213-222 Blending Bayesian and Classical Tools to Define Optimal Sample-Size-Dependent Significance Levels
by Mark Andrew Gannon & Carlos Alberto de Bragança Pereira & Adriano Polpo - 223-234 How Effect Size (Practical Significance) Misleads Clinical Practice: The Case for Switching to Practical Benefit to Assess Applied Research Findings
by Stanley Pogrow - 235-245 Abandon Statistical Significance
by Blakeley B. McShane & David Gal & Andrew Gelman & Christian Robert & Jennifer L. Tackett - 246-261 Statistical Inference Enables Bad Science; Statistical Thinking Enables Good Science
by Christopher Tong - 262-270 Inferential Statistics as Descriptive Statistics: There Is No Replication Crisis if We Don’t Expect Replication
by Valentin Amrhein & David Trafimow & Sander Greenland - 271-280 The New Statistics for Better Science: Ask How Much, How Uncertain, and What Else Is Known
by Robert J. Calin-Jageman & Geoff Cumming - 281-290 How Large Are Your G-Values? Try Gosset’s Guinnessometrics When a Little “p” Is Not Enough
by Stephen T. Ziliak - 291-295 Predictive Inference and Scientific Reproducibility
by Dean Billheimer - 296-304 Treatment Choice With Trial Data: Statistical Decision Theory Should Supplant Hypothesis Testing
by Charles F. Manski - 305-311 Trial Size for Near-Optimal Choice Between Surveillance and Aggressive Treatment: Reconsidering MSLT-II
by Charles F. Manski & Aleksey Tetenov - 312-318 Frequentist, Bayes, or Other?
by Michael Lavine - 319-327 Inference and Decision Making for 21st-Century Drug Development and Approval
by Stephen J. Ruberg & Frank E. Harrell & Margaret Gamalo-Siebers & Lisa LaVange & J. Jack Lee & Karen Price & Carl Peck - 328-339 Multiple Perspectives on Inference for Two Simple Statistical Scenarios
by Noah N. N. van Dongen & Johnny B. van Doorn & Quentin F. Gronau & Don van Ravenzwaaij & Rink Hoekstra & Matthias N. Haucke & Daniel Lakens & Christian Hennig & Richard D. Morey & Saskia Homer & Andrew Gelman & Jan Sprenger & Eric-Jan Wagenmakers - 340-345 Five Nonobvious Changes in Editorial Practice for Editors and Reviewers to Consider When Evaluating Submissions in a Post p
by David Trafimow - 346-351 The Impact of Results Blind Science Publishing on Statistical Consultation and Collaboration
by Joseph J. Locascio - 352-357 Coup de Grâce for a Tough Old Bull: “Statistically Significant” Expires
by Stuart H. Hurlbert & Richard A. Levine & Jessica Utts - 358-373 The World of Research Has Gone Berserk: Modeling the Consequences of Requiring “Greater Statistical Stringency” for Scientific Publication
by Harlan Campbell & Paul Gustafson - 374-384 Assessing the Statistical Analyses Used in Basic and Applied Social Psychology After Their p-Value Ban
by Ronald D. Fricker & Katherine Burke & Xiaoyan Han & William H. Woodall - 385-391 Content Audit for p-value Principles in Introductory Statistics
by Karsten Maurer & Lynette Hudiburgh & Lisa Werwinski & John Bailer - 392-401 Beyond Calculations: A Course in Statistical Thinking
by E. Ashley Steel & Martin Liermann & Peter Guttorp
October 2019, Volume 73, Issue 4
- 313-320 Test for Trend With a Multinomial Outcome
by Aniko Szabo - 321-326 A Five-Decision Testing Procedure to Infer the Value of a Unidimensional Parameter
by Aaron McDaid & Zoltán Kutalik & Valentin Rousson - 327-339 A Bayes Factor for Replications of ANOVA Results
by Christopher Harms - 340-349 Bias Reduction in Logistic Regression with Missing Responses When the Missing Data Mechanism is Nonignorable
by Arnab Kumar Maity & Vivek Pradhan & Ujjwal Das - 350-359 Power and Sample Size for Fixed-Effects Inference in Reversible Linear Mixed Models
by Yueh-Yun Chi & Deborah H. Glueck & Keith E. Muller - 360-366 A Comparative Review of Nonparametric Statistics Textbooks
by Alice Richardson - 367-374 Demystifying the Integrated Tail Probability Expectation Formula
by Ambrose Lo - 375-384 Key Attributes of a Modern Statistical Computing Tool
by Amelia McNamara - 385-399 Modeling Efficiency of Foreign Aid Allocation in Malawi
by Philip A. White & Candace Berrett & E. Shannon Neeley-Tass & Michael G. Findley - 400-407 We Stand on the Shoulders of Giants—Pioneers of Statistics in Industry
by Ronald D. Snee - 408-410 On the Mean Value Theorem for Estimating Functions
by Alexandre Galvão Patriota - 411-412 Comment on VanDerwerken (2019)
by Jesse Frey - 413-414 The Other Arbitrary Cutoff
by Peter Bacchetti - 415-416 Handbook of Educational Measurement and Psychometrics Using R
by Anelise G. Sabbag - 416-417 Randomistas: How Radical Researchers Are Changing Our World
by Megan D. Higgs - 418-419 Stochastic Processes: From Applications to Theory
by Christian Litterer - 420-420 Correction
by The Editors - 420-421 Editorial Collaborators
by The Editors
July 2019, Volume 73, Issue 3
- 213-223 Disease Mapping With Generative Models
by Feifei Wang & Jian Wang & Alan E. Gelfand & Fan Li - 224-231 Evaluating Wikipedia as a Self-Learning Resource for Statistics: You Know They'll Use It
by Peter K. Dunn & Margaret Marshman & Robert McDougall - 232-242 A Cheap Trick to Improve the Power of a Conservative Hypothesis Test
by Thomas J. Fisher & Michael W. Robbins - 243-252 What Properties Might Statistical Inferences Reasonably be Expected to Have?—Crisis and Resolution in Statistical Inference
by Geoffrey K. Robinson - 253-263 Who Wants to be a Statistician? An Analysis of ACT-Tested Public School Students
by Jeff Allen - 264-272 The Analysis of Survey Data with Framing Effects
by Jacob Goldin & Daniel Reck - 273-277 Inducing Any Feasible Level of Correlation to Bivariate Data With Any Marginals
by Hakan Demirtas - 278-281 Sharpening Jensen's Inequality
by J. G. Liao & Arthur Berg - 282-287 Practical Teaching Strategies for Hypothesis Testing
by Ryoungsun Park - 288-295 Exploring the Equivalence of Two Common Mixture Models for Duration Data
by Peter S. Fader & Bruce G. S. Hardie & Daniel McCarthy & Ramnath Vaidyanathan - 296-306 Joint Clustering With Correlated Variables
by Hongmei Zhang & Yubo Zou & Will Terry & Wilfried Karmaus & Hasan Arshad - 307-309 R-squared for Bayesian Regression Models
by Andrew Gelman & Ben Goodrich & Jonah Gabry & Aki Vehtari - 310-311 Displaying Time Series, Spatial, and Space-Time Data with R, 2nd ed
by Silas Bergen - 312-312 Letter to the Editor
by Thaddeus Tarpey & Eva Petkova
April 2019, Volume 73, Issue 2
- 109-116 Leadership in Statistics: Increasing Our Value and Visibility
by Eric W. Gibson - 117-125 Revisiting Nested Group Testing Procedures: New Results, Comparisons, and Robustness
by Yaakov Malinovsky & Paul S. Albert - 126-140 Bayesian Analysis on a Noncentral Fisher–Student’s Hypersphere
by Richard Le Blanc - 141-150 Randomization Inference for Outcomes with Clumping at Zero
by Luke Keele & Luke Miratrix - 151-158 A Method to Handle Zero Counts in the Multinomial Model
by Frank Tuyl - 159-164 Near-Balanced Incomplete Block Designs, With an Application to Poster Competitions
by Xiaoyue Niu & James L. Rosenberger - 165-178 A Primer on Visualizations for Comparing Populations, Including the Issue of Overlapping Confidence Intervals
by Tommy Wright & Martin Klein & Jerzy Wieczorek - 179-185 A Starting Point for Navigating the World of Daily Fantasy Basketball
by Charles South & Ryan Elmore & Andrew Clarage & Rob Sickorez & Jing Cao - 186-190 Teaching Bayes’ Theorem: Strength of Evidence as Predictive Accuracy
by Jeffrey N. Rouder & Richard D. Morey - 191-194 Higher-Order Moments Using the Survival Function: The Alternative Expectation Formula
by Subhabrata Chakraborti & Felipe Jardim & Eugenio Epprecht - 195-199 A Note on Bias of Closed-Form Estimators for the Gamma Distribution Derived From Likelihood Equations
by Francisco Louzada & Pedro L. Ramos & Eduardo Ramos - 200-207 A Graphical Tool for Interpreting Regression Coefficients of Trinomial Logit Models
by Flavio Santi & Maria Michela Dickson & Giuseppe Espa - 208-208 Statistical Analysis of Contingency Tables
by Anna Schenfisch & Brittany Fasy - 208-209 Business Survival Analysis Using SAS: An Introduction to Lifetime Probabilities
by Xin Wang - 209-210 Quantitative Methods for HIV/AIDS Research
by Nicole Bohme Carnegie - 210-211 Clinical Trial Optimization Using R
by Emily Dressler - 211-212 Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS
by Minggen Lu
January 2019, Volume 73, Issue 1
- 1-3 Why are p-Values Controversial?
by Todd A. Kuffner & Stephen G. Walker - 4-9 Asymptotic Properties of Marginal Least-Square Estimator for Ultrahigh-Dimensional Linear Regression Models with Correlated Errors
by Gyuhyeong Goh & Dipak K. Dey - 10-15 Invariance, Optimality, and a 1-Observation Confidence Interval for a Normal Mean
by Stephen Portnoy - 16-21 On An Intriguing Distributional Identity
by M. C. Jones & Éric Marchand & William E. Strawderman - 22-31 Comparing Objective and Subjective Bayes Factors for the Two-Sample Comparison: The Classification Theorem in Action
by Mithat Gönen & Wesley O. Johnson & Yonggang Lu & Peter H. Westfall - 32-42 The Perils of Balance Testing in Experimental Design: Messy Analyses of Clean Data
by Diana C. Mutz & Robin Pemantle & Philip Pham - 43-49 Modified Wilcoxon–Mann–Whitney Test and Power Against Strong Null
by Youyi Fong & Ying Huang - 50-55 Enriching Students’ Conceptual Understanding of Confidence Intervals: An Interactive Trivia-Based Classroom Activity
by Xiaofei Wang & Nicholas G. Reich & Nicholas J. Horton - 56-60 Sum of a Random Number of Correlated Random Variables that Depend on the Number of Summands
by Joel E. Cohen - 61-69 Teaching Communication in a Statistical Collaboration Course: A Feasible, Project-Based, Multimodal Curriculum
by Mario A. Davidson & Charlene M. Dewey & Amy E. Fleming - 70-79 Simple Measures of Individual Cluster-Membership Certainty for Hard Partitional Clustering
by Dongmeng Liu & Jinko Graham - 80-88 An Examination of Discrepancies in Multiple Imputation Procedures Between SAS® and SPSS®
by Jianjun Wang & Dallas E. Johnson - 89-93 Phlegon's Stem-and-Leaf Display
by Spyros Missiakoulis - 94-104 blogdown: Creating Websites With R Markdown
by Megan D. Higgs & Xiaoke Zhang & Angelo Elmi & James M. Flegal & Jessica Utts & Sandra E. Safo & Craig A. Rolling & Michael J. Higgins & Jingyi Jessica Li - 105-105 Letter to the Editor
by M.C. Jones - 106-108 Editorial Collaborators
by The Editors
October 2018, Volume 72, Issue 4
- 303-308 Bayesian Inference for Kendall’s Rank Correlation Coefficient
by Johnny van Doorn & Alexander Ly & Maarten Marsman & Eric-Jan Wagenmakers - 309-314 Optimal Whitening and Decorrelation
by Agnan Kessy & Alex Lewin & Korbinian Strimmer - 315-320 A “Paradox” in Confidence Interval Construction Using Sufficient Statistics
by Weizhen Wang - 321-327 A Survey of Reporting Practices of Computer Simulation Studies in Statistical Research
by Michael Harwell & Nidhi Kohli & Yadira Peralta-Torres - 328-343 A Simple and Effective Inequality Measure
by Luke A. Prendergast & Robert G. Staudte - 344-347 On Mixture Alternatives and Wilcoxon’s Signed-Rank Test
by Jonathan D. Rosenblatt & Yoav Benjamini - 348-353 An Improved Boxplot for Univariate Data
by M. L. Walker & Y. H. Dovoedo & S. Chakraborti & C. W. Hilton - 354-358 An Innovative Classroom Approach for Developing Critical Thinkers in the Introductory Statistics Course
by Sherri Cheng & Mark Ferris & Jessica Perolio - 359-367 Teaching Ethics in a Statistics Curriculum with a Cross-Cultural Emphasis
by Alan C. Elliott & S. Lynne Stokes & Jing Cao - 368-375 A Bayesian Survival Analysis of a Historical Dataset: How Long Do Popes Live?
by Julian Stander & Luciana Dalla Valle & Mario Cortina-Borja - 376-378 Taylor's Law Holds for Finite OEIS Integer Sequences and Binomial Coefficients
by Simon Demers - 379-381 Model Selection and Regression -Statistics
by DeWayne Derryberry & Ken Aho & John Edwards & Teri Peterson - 382-391 A Guide to Teaching Data Science
by Stephanie C. Hicks & Rafael A. Irizarry - 392-393 Comment on Knaeble and Dutter (2017)
by Ronald Christensen - 394-394 Corrigenda
by The Editors
July 2018, Volume 72, Issue 3
- 213-218 Minimum Volume Confidence Sets for Two-Parameter Exponential Distributions
by Jin Zhang - 219-238 Testing for Serial Independence: Beyond the Portmanteau Approach
by Luca Bagnato & Lucio De Capitani & Antonio Punzo - 239-252 Structural Equation Models for Dealing With Spatial Confounding
by Hauke Thaden & Thomas Kneib - 253-264 Predicting Home Run Production in Major League Baseball Using a Bayesian Semiparametric Model
by Gilbert W. Fellingham & Jared D. Fisher - 265-277 The Landscape of Causal Inference: Perspective From Citation Network Analysis
by Weihua An & Ying Ding