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1. Evidencebased statistics [2021]
 Cahusac, Peter, 1957 author.
 Hoboken, NJ : Wiley, [2021].
 Description
 Book — 1 online resource.
 Summary

 The Evidence is the Evidence
 The Evidential Approach
 Two Samples
 ANOVA
 Correlation and Regression
 Categorical Data
 Nonparametric Analyses
 Other Useful Techniques
 Orthogonal Polynomials
 Occam's Bonus
 Problems with p Values.
 Takeuchi, Kei, 1933
 Tokyo, Japan : Springer, [2020]
 Description
 Book — 1 online resource (428 pages)
 Summary

 Part I Statistical Prediction. 1 Theory of Statistical Prediction. Part II Unbiased Estimation. 2 Unbiased Estimation in Case of the Class of Distributions of Finite Rank. 3 Some Theorems on Invariant Estimators of Location. Part III Robust Estimation. 4 Robust Estimation and Robust Parameter. 5 Robust Estimation of Location in the Case of Measurement of Physical Quantity. 6 A Uniformly Asymptotically Efficient Estimator of a Location Parameter. Part IV Randomization. 7 Theory of Randomized Designs. 8 Some Remarks on General Theory for Unbiased Estimation of a Real Parameter of a Finite Population. Part V Tests of Normality. 9 The Studentized Empirical Characteristic Function and Its Application to Test for the Shape of Distribution. 10 Tests of Univariate Normality. 11 The Tests for Multivariate Normality. Part VI Model Selection. 12 On the Problem of Model Selection Based on the Data.Part VII Asymptotic Approximation. 13 On Sum of 01 Random Variables (I. Univariate Case). 14 On Sum of 01 Random Variables (II. Multivariate Case). 15 Algebraic Properties and Validity of Univariate and Multivariate CornishFisher Expansion.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
3. Eserciziario di Statistica Inferenziale [2020]
 Gasperoni, Francesca, author.
 Milano : Springer, 2020.
 Description
 Book — 1 online resource (ix, 271 pages) : illustrations
 Summary

 Intro
 Prefazione
 Indice
 Parte I Statistica inferenziale
 1 Fondamenti di probabilità e statistica
 1.1 Richiami di teoria
 1.2 Esercizi
 1.3 Soluzioni
 2 Statistiche sufficienti, minimali e complete
 2.1 Richiami di teoria
 2.2 Esercizi
 2.3 Soluzioni
 3 Stimatori puntuali
 3.1 Richiami di teoria
 3.2 Esercizi
 3.3 Soluzioni
 4 Uniform Minimum Variance Unbiased Estimators (UMVUE)
 4.1 Richiami di teoria
 4.2 Esercizi
 4.3 Soluzioni
 5 Likelihood Ratio Test
 5.1 Richiami di teoria
 5.2 Esercizi
 5.3 Soluzioni
 6 Test uniformemente più potente
 6.1 Richiami di teoria
 6.2 Esercizi
 6.3 Soluzioni
 7 Intervalli di confidenza
 7.1 Richiami di teoria
 7.2 Esercizi
 7.3 Soluzioni
 8 Statistica asintotica
 8.1 Richiami di teoria
 8.2 Esercizi
 8.3 Soluzioni
 Parte II Modelli di regressione e analisi della varianza
 9 Regressione lineare
 9.1 Richiami di teoria
 9.2 Esercizi
 9.3 Soluzioni
 10 Modelli lineari generalizzati
 10.1 Richiami di teoria
 10.2 Esercizi
 10.3 Soluzioni
 11 ANOVA: analisi della varianza
 11.1 Richiami di teoria
 11.2 Esercizi
 11.3 Soluzioni
 12 Esercizi di riepilogo
 12.1 Esercizi
 12.2 Soluzioni
 Distribuzioni di probabilità
 Bibliografia
 Panaretos, Victor M.
 Cham : Springer, 2020.
 Description
 Book — 1 online resource
 Summary

 Optimal transportation. The Wasserstein space. Frechet means in the Wasserstein space. Phase variation and Frechet means. Construction of Frechet means and multicouplings.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
5. Power laws : a statistical trek [2020]
 Eliazar, Iddo.
 Cham : Springer, 2020.
 Description
 Book — 1 online resource
 Summary

 Introduction. From lognormal to power. The Poisson law. Framework. Threshold analysis. Hazard rates. Order statistics. Exponent estimation. Socioeconomic analysis. Fractality. Sums. Dynamics. Limit laws. First digits. Back to lognormal. Conclusion. Appendix.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Wolfe, Douglas A.
 Cham, Switzerland : Springer, 2020.
 Description
 Book — 1 online resource
 Summary

  Introduction.  Basic Probability.  Random Variables and Probability Distributions.  General Properties of Random Variables.  Joint Probability Distributions for Two Random Variables.  Probability Distribution of a Function of a Single Random Variable.  Sampling Distributions.  Asymptotic (LargeSample) Properties of Statistics.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
7. Statistical analysis of empirical data [electronic resource] : methods for applied sciences [2020]
 Pardo, Scott.
 Cham : Springer, 2020.
 Description
 Book — 1 online resource (278 p.) Digital: text file; PDF.
 Summary

 Chapter 1: Fundamentals.
 Chapter 2: Sample Statistics are NOT Parameters.
 Chapter 3: Confidence.
 Chapter 4: Multiplicity and Multiple Comparisons.
 Chapter 5: Power and the Myth of Sample Size Determination.
 Chapter 6: Regression and Model Fitting with Collinearity.
 Chapter 7: Overparameterization.
 Chapter 8: Ignoring Error Control Factors and Experimental Design.
 Chapter 9: Generalized Linear Models.
 Chapter 10: Mixed Models and Variance Components.
 Chapter 11: Models, Models Everywhere...Model Selection.
 Chapter 12: Bayesian Analyses.
 Chapter 13: The Acceptance Sampling Game.
 Chapter 14: Nonparametric Statistics  A Strange Name.
 Chapter 15: Autocorrelated Data and Dynamic Systems.
 Chapter 16: Multivariate Analysis and Classification.
 Chapter 17: TimetoEvent: Survival and Life Testing. Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
8. Statistical data analysis and entropy [2020]
 Eshima, Nobuoki.
 Singapore : Springer, 2020.
 Description
 Book — 1 online resource (263 pages) Digital: text file; PDF.
 Summary

 Entropy and basic statistics. Analysis of the association in twoway contingency tables. Analysis of the association in multiway contingency tables. Analysis of continuous variables.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Dörre, Achim, author.
 Singapore : Springer, [2019]
 Description
 Book — 1 online resource
 Summary

 Chapter 1: Introduction to doubletruncation.
 Chapter 2: Parametric inference under special exponential family.
 Chapter 3: Parametric inference under locationscale family.
 Chapter 4: Bayes inference.
 Chapter 5: Nonparametric inference.
 Chapter 6: Linear regression. Appendix A: Data (if German company data are available). Appendix B: R codes for inference under exponential family. Appendix C: R codes for inference under locationscale family. Appendix D: R codes for Bayes inference. Appendix E: R codes for linear regression.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
10. Euclidean design theory [2019]
 Sawa, Masanori, author.
 Singapore : Springer, [2019]
 Description
 Book — 1 online resource.
 Summary

 Chapter I: Reproducing Kernel Hilbert Space
 Chapter II: Cubature Formula
 Chapter III: Optimal Euclidean Design
 Chapter IV: Constructions of Optimal Euclidean Design
 Chapter V: Euclidean Design Theory.
11. A graduate course on statistical inference [2019]
 Li, Bing, 1960 author.
 New York : Springer, [2019]
 Description
 Book — 1 online resource : illustrations.
 Summary

 1. Probability and Random Variables.
 2. Classical Theory of Estimation.
 3. Testing Hypotheses in the Presence of Nuisance Parameters.
 4. Testing Hypotheses in the Presence of Nuisance Parameters.
 5. Basic Ideas of Bayesian Methods.
 6. Bayesian Inference.
 7. Asymptotic Tools and Projections.
 8. Asymptotic Theory for Maximum Likelihood Estimation.
 9. Estimating Equations.
 10. Convolution Theorem and Asymptotic Efficiency.
 11. Asymptotic Hypothesis Test. References. Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Martin, Ole.
 Wiesbaden : Springer Spektrum, 2019.
 Description
 Book — 1 online resource (328 p.).
 Summary

 Laws of Large Numbers. Random Observation Schemes. Bootstrapping Asymptotic Laws. Testing for (Common) Jumps.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Popping, R. (Roel), author.
 Cham, Switzerland : Springer, [2019]
 Description
 Book — 1 online resource (156 p.) Digital: text file; PDF.
 Summary

 Introduction. Reliability and Validity. Interrater Agreement. Indices. References. Index. Notation.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
14. Introduction to mathematical statistics [2019]
 Hogg, Robert V. author.
 Eighth edition.  Boston : Pearson, [2019]
 Description
 Book — xiii, 746 pages ; 26 cm
 Online
Science Library (Li and Ma)
Science Library (Li and Ma)  Status 

Stacks  Request (opens in new tab) 
QA276 .H59 2019  Unavailable Checked out  Overdue 
 Komori, Osamu, author.
 Tokyo, Japan : Springer, [2019]
 Description
 Book — viii, 59 pages : illustrations (some color), color maps ; 23 cm.
 Summary

 1. Imbalance Data.
 2. Weighted Logistic Regression.
 3. BetaMaxent.
 4. Generalizedt Statistic.
 5. Machine Learning Methods for Imbalance Data.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
Marine Biology Library (Miller)
Marine Biology Library (Miller)  Status 

Stacks  
QA276 .K627 2019  Unknown 
 Cham : Springer, 2019.
 Description
 Book — 1 online resource (409 pages).
 Summary

 Part I. Statistical Process Control.
 Chapter 1. Some Recent Studies in Statistical Process Control.
 Chapter 2. Statistical Quality Control And Reliability Analysis Using the BirnbaumSaunders Distribution with Industrial Applications.
 Chapter 3. Statistical System Monitoring (SSM) for EnterpriseLevel Quality Control.
 Chapter 4. Enhanced Cumulative Sum Charts based on Ranked Set Sampling.
 Chapter 5. A Survey of Control Charts for Simple Linear Profile Processes with Authcorrelation.
 Chapter 6. Sequential Monitoring of Circular processes related to the von Mises Distribution. Part II. Acceptance Sampling Plans.
 Chapter 7. Time Truncated Life Test Using the Generalized Multiple Dependent State Sampling plans for Various Life Distributions.
 Chapter 8. Decision Theoretic Sampling Plan for Oneparameter Exponential Distribution under TypeI and TypeI Hybrid Censoring Schemes.
 Chapter 9. Economical Sampling Plans with Warranty.
 Chapter 10. Design of Reliability Acceptance Sampling Plans under Partially Accelerated Life Test. Part III. Reliability Testing and Designs.
 Chapter 11. Bayesian Sequential Design Based on Dual Objectives for Accelerated Life Tests.
 Chapter 12. The Stressstrength Models for the Proportional Hazards Family and Proportional Reverse Hazards Family.
 Chapter 13. A Degradation Based on the Wiener Process Assuming nonnormal Distributed Measurement Errors.
 Chapter 14. An Introduction of Generalized Linear Model Approach to Accelerated Life Test Planning with TypeI Censoring.
 Chapter 15. Robust Design in the Case of Data Contamination and Model Departure.
 Chapter 16. Defects Driven Yield and Reliability Modeling for Semiconductor Manufacturing.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Herzog, Michael H. author.
 Cham, Switzerland : Springer, 2019.
 Description
 Book — 1 online resource (xi, 142 pages) : illustrations (some color).
 Summary

 Part I
 Basic Probability Theory
 Experimental Design and the Basics of Statistics: Signal detection Theory (SDT)
 The Core Concept of Statistics
 Variations on the ttest
 PART II
 The Multiple Testing Problem
 ANOVA
 Experimental design: Model Fits, Power, and Complex Designs
 Correlation
 PART III
 Metaanalysis
 Understanding replication
 Magnitude of excess success
 Suggested improvements and challenges.
 Cham, Switzerland : Springer, 2018.
 Description
 Book — 1 online resource (xvii, 242 pages) : illustrations (some color).
 Summary

 Rank Properties for Centred Threeway Arrays  C. Albers (Univ. of Groningen) et al. Principal Component Analysis of Complex Data and Application to Climatology  S. Camiz (La Sapienza Univ. of Rome) et al. Clustering upper level units in multilevel models for ordinal data  L. Grilli (Univ. of Florence) et al. A Multilevel Heckman Model To Investigate Financial Assets Among Old People In Europe  O. Paccagnella (univ. of Padua) et al. Multivariate stochastic downscaling with semicontinuous data  L. Paci (univ. of Bologna) et al. Motivations and expectations of students' mobility abroad: a mapping technique  V. Caviezel (Univ. of Bergamo) et al. Comparing multistep ahead forecasting functions for time series clustering  M. Corduas (Univ. of Naples Federico II) et al. Electre TriMachine Learning Approach to the Record Linkage  V. Minnetti (La Sapienza Univ. of Rome) et al. . MCA Based Community Detection  C. Drago (Univ. of Rome Niccolo Cusano). Classi fying social roles by network structures  S. Gozzo (univ. of Catania) et al. Bayesian Networks For Financial Markets Signals Detection  A. Greppi (univ.of Pavia) et al. Finite sample behaviour of MLE in network autocorrelation models  M. La Rocca (Univ. of Salerno) et al. Classification Models as Tools of Bankruptcy Prediction  Polish Experience  J. Pochiecha (Cracow university) et al. Clustering macroseismic fields by statistical data depth functions  C. Agostinelli (Univ. of Trento). Depth based tests for circular antipodal symmetry  G. Pandolfo (Univ. of Cassino) et al. Estimating The Effect Of Prenatal Care On Birth Outcomes  E. Sironi (Sacro Cuore University) et al. Bifurcations And Sunspots In Continuous Time Optimal Models With Externalities  B.Venturi (Univ. of Cagliari) et al. Enhancing Big Data Exploration with Faceted Browsing  S. Bergamaschi (Univ. of Modena and Reggio Emilia) et al. Big data meet pharmaceutical industry: an application on social media data  C. Liberati (Univ. of Milan Bicocca) et al. From Big Data to information: statistical issues through a case study  S. Signorelli (Univ. of Bergamo) et al. Quality of Classification approaches for the quantitative analysis of international conflict  A.F.X. Wilhelm (Jacobs Univ. Bremen). Psplines based clustering as a general framework: some applications using different clustering algorithms  C. Iorio (Univ. of Naples Federico II) et al. A graphical copulabased tool for detecting tail dependence  R. Pappada (univ. of Trieste) et al. Comparing spatial and spatiotemporal FPCA to impute large continuous gaps in space  M. Ruggeri (Univ. of Palermo) et al. Exploring Italian students' performances in the SNV test: a quantile regression perspective  A. Costanzo (National Institute for the Evaluation of Education and Training  INVALSI) et al.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Cham, Switzerland : Springer, [2018]
 Description
 Book — 1 online resource.
20. Mathematics Applied in Information Systems [2018]
 Ram, Mangey.
 Sharjah : Bentham Science Publishers, 2018.
 Description
 Book — 1 online resource (299 pages)
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