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1. Le logiciel R : Maîtriser le langage Effectuer des analyses statistiques
by Pierre Lafaye Micheaux, Rémy Drouilhet, Benoît Liquet
出版情報: Paris : Springer-Verlag France, 2011
シリーズ名: Statistique et probabilités appliquées ;
オンライン: http://dx.doi.org/10.1007/978-2-8178-0115-5
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2. Analyse statistique des risques agro-environnementaux : Études de cas
by David Makowski, Hervé Monod
出版情報: Paris : Springer Paris, 2011
シリーズ名: Collection Statistique et probabilités appliquées ;
オンライン: http://dx.doi.org/10.1007/978-2-8178-0251-0
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3. COMPSTAT 2008 : Proceedings in Computational Statistics
edited by Paula Brito
出版情報: Heidelberg : Physica-Verlag Heidelberg, 2008
オンライン: http://dx.doi.org/10.1007/978-3-7908-2084-3
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4. A Beginner's Guide to R
by Alain F. Zuur, Elena N. Ieno, Erik Meesters
出版情報: New York, NY : Springer-Verlag New York, 2009
シリーズ名: Use R ;
オンライン: http://dx.doi.org/10.1007/978-0-387-93837-0
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5. Medical Applications of Finite Mixture Models
by Peter Schlattmann
出版情報: Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2009
シリーズ名: Statistics for Biology and Health ;
オンライン: http://dx.doi.org/10.1007/978-3-540-68651-4
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6. Maîtriser l’aléatoire : Exercices résolus de probabilités et statistique. Deuxième edition
by Eva Cantoni, Philippe Huber, Elvezio Ronchetti
出版情報: Paris : Springer-Verlag Paris, 2009
シリーズ名: Statistique et probabilités appliquées ;
オンライン: http://dx.doi.org/10.1007/978-2-287-99671-9
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7. Six Sigma with R : Statistical Engineering for Process Improvement
by Emilio L. Cano, Javier M. Moguerza, Andrés Redchuk
出版情報: New York, NY : Springer New York : Imprint: Springer, 2012
シリーズ名: Use R! ; 36
オンライン: http://dx.doi.org/10.1007/978-1-4614-3652-2
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目次情報: 続きを見る
Part I Basics
Six Sigma in a Nutshell
R from the Beginning
Part II R Tools for the Define phase
Process Mapping with R
Loss Function Analysis with R
Part III R Tools for the Measure phase
Measurement System Analysis with R
Pareto Analysis with R
Process Capability Analysis with R
Part IV R Tools for the Analyze phase
Charts with R
Statistics and Probability with R
Statistical Inference with R
Part V R Tools for the Improve phase
Design of Experiments with R
Part VI R Tools for the Control phase
Process Control with R
Part VII Further and Beyond
Other Tools and Methodologies
Part I Basics
Six Sigma in a Nutshell
R from the Beginning
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8. Excel 2010 for Biological and Life Sciences Statistics : A Guide to Solving Practical Problems
by Thomas J. Quirk, Meghan Quirk, Howard Horton
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
オンライン: http://dx.doi.org/10.1007/978-1-4614-5779-4
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9. Excel 2007 for Biological and Life Sciences Statistics : A Guide to Solving Practical Problems
by Thomas J. Quirk, Meghan Quirk, Howard Horton
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
オンライン: http://dx.doi.org/10.1007/978-1-4614-6003-9
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Sample Size, Mean, Standard Deviation, and Standard Error of the Mean
Random Number Generator
Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing
One-Group t-Test for the Mean
Two-Group t-Test of the Difference of the Means for Independent Groups
Correlation and Simple Linear Regression
Multiple Correlation and Multiple Regression
One-Way Analysis of Variance (ANOVA)
Appendix A:  Answers to End-of-Chapter Practice Problems
Appendix B:  Practice Test
Appendix C:  Answers to Practice Test
Appendix D:  Statistical Formulas
Appendix E:  t-table
Index
Sample Size, Mean, Standard Deviation, and Standard Error of the Mean
Random Number Generator
Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing
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10. Applied Predictive Modeling
by Max Kuhn, Kjell Johnson
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
オンライン: http://dx.doi.org/10.1007/978-1-4614-6849-3
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目次情報: 続きを見る
General Strategies
Regression Models
Classification Models
Other Considerations
Appendix
References
Indices
General Strategies
Regression Models
Classification Models
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11. mODa 10 – Advances in Model-Oriented Design and Analysis : Proceedings of the 10th International Workshop in Model-Oriented Design and Analysis Held in Łagów Lubuski, Poland, June 10–14, 2013
edited by Dariusz Ucinski, Anthony C. Atkinson, Maciej Patan
出版情報: Heidelberg : Springer International Publishing : Imprint: Springer, 2013
シリーズ名: Contributions to Statistics ;
オンライン: http://dx.doi.org/10.1007/978-3-319-00218-7
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A Convergent Algorithm for Finding KL-Optimum Designs and Related Properties
Robust Experimental Design for Choosing Between Models of Enzyme Inhibition
Checking Linear Regression Models Taking Time into Account
Optimal Sample Proportion for a Two-Treatment Clinical Trial in the Presence of Surrogate Endpoints
Estimating and Quantifying Uncertainties on Level Sets Using the Vorobev Expectation and Deviation with Gaussian Process Models
Optimal Designs for Multiple-Mixture by Process Variable Experiments
Optimal Design of Experiments for Delayed Responses in Clinical Trials
Construction of Minimax Designs for the Trinomial Spike Model in Contingent Valuation Experiments
Maximum Entropy Design in High Dimensions by Composite Likelihood Modelling
Randomization Based Inference for the Drop-The-Loser Rule
Adaptive Bayesian Design with Penalty Based on Toxicity-Efficacy Response
Randomly Reinforced Urn Designs Whose Allocation Proportions Converge to Arbitrary Prespecified Values
Kernels and Designs for Modelling Invariant Functions: From Group Invariance to Additivity
Optimal Design for Count Data with Binary Predictors in Item Response Theory
Differences between Analytic and Algorithmic Choice Designs for Pairs of Partial Profiles
Approximate Bayesian Computation Design (ABCD), An Introduction
Approximation of the Fisher Information Matrix for Nonlinear Mixed Effects Models in Population Pk/Pd Studies
c-Optimal Designs for the Bivariate Emax Model
On the Functional Approach to Locally D-Optimum Design for Multiresponse Models
Sample Size Calculation for Diagnostic Tests in Generalized Linear Mixed Models
D-Optimal Designs for Lifetime Experiments with Exponential Distribution and Censoring
Convergence of An Algorithm for Constructing Minimax Designs
Extended Optimality Criteria for Optimum Design in Nonlinear Regression
Optimal Design for Multivariate Models with Correlated Observations
Optimal Designs for the Prediction of Individual Effects in Random Coefficient Regression
D-Optimum Input Signals for Systems with Spatio-Temporal Dynamics
Random Projections in Model Selection and Related Experimental Design Problems
Optimal Design for the Bounded Log-Linear Regression Model
A Convergent Algorithm for Finding KL-Optimum Designs and Related Properties
Robust Experimental Design for Choosing Between Models of Enzyme Inhibition
Checking Linear Regression Models Taking Time into Account
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12. Risk Assessment and Evaluation of Predictions
edited by Mei-Ling Ting Lee, Mitchell Gail, Ruth Pfeiffer, Glen Satten, Tianxi Cai, Axel Gandy
出版情報: New York, NY : Springer New York : Imprint: Springer, 2013
シリーズ名: Lecture Notes in Statistics ; 210
オンライン: http://dx.doi.org/10.1007/978-1-4614-8981-8
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目次情報:
Preface
Methods for Evaluating Prediction Performance of Biomarkers and Tests
Multiple Imputation Approach for Surrogate Marker Evaluation in the Principal Strati cation Causal Inference Framework
Preface
Methods for Evaluating Prediction Performance of Biomarkers and Tests
Multiple Imputation Approach for Surrogate Marker Evaluation in the Principal Strati cation Causal Inference Framework
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13. German-Japanese Interchange of Data Analysis Results
edited by Wolfgang Gaul, Andreas Geyer-Schulz, Yasumasa Baba, Akinori Okada
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2014
シリーズ名: Studies in Classification, Data Analysis, and Knowledge Organization ;
オンライン: http://dx.doi.org/10.1007/978-3-319-01264-3
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目次情報:
Clustering
Analysis of Data and Models
Applications
Clustering
Analysis of Data and Models
Applications
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14. Introduction to Data Analysis and Graphical Presentation in Biostatistics with R : Statistics in the Large
by Thomas W. MacFarland
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2014
シリーズ名: SpringerBriefs in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-3-319-02532-2
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Introduction to Biostatistics and R
Data exploration, descriptive statistics and measures of central tendency
Student's t-Test for independent samples
Student's t-Test for matched pairs
One way ANOVA
Two way ANOVA
Correlation and linear regression
Future Actions and Next Steps
Introduction to Biostatistics and R
Data exploration, descriptive statistics and measures of central tendency
Student's t-Test for independent samples
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15. Applied Statistical Methods in Agriculture, Health and Life Sciences
by Bayo Lawal
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2014
オンライン: http://dx.doi.org/10.1007/978-3-319-05555-8
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Table of Contents attached as well. Introduction
Frequency Distributions
Numerical Description of Data
Probability and Probability Distributions
Estimation and Hypothesis Testing
Regression Analysis
Categorical Data Analysis
Experimental Design
The Completely Randomized Design
The Randomized Complete Block Design
Multiple Blocking Designs
Analysis of Covariance
Factorial Treatments Designs
The Split-Plot Design
Incomplete Block Design
Quantal-Bioassay
Repeated Measures Design
Survival Analysis
Table of Contents attached as well. Introduction
Frequency Distributions
Numerical Description of Data
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16. Bayesian Nonparametric Data Analysis
by Peter Müller, Fernando Andres Quintana, Alejandro Jara, Tim Hanson
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2015
シリーズ名: Springer Series in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-3-319-18968-0
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目次情報: 続きを見る
Preface
Acronyms
1.Introduction
2.Density Estimation - DP Models
3.Density Estimation - Models Beyond the DP
4.Regression
5.Categorical Data
6.Survival Analysis
7.Hierarchical Models
8.Clustering and Feature Allocation
9.Other Inference Problems and Conclusions
Appendix: DP package
Preface
Acronyms
1.Introduction
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17. Maîtriser l’aléatoire : Exercices résolus de probabilités et statistique
by Eva Cantoni, Elvezio Ronchetti, Philippe Huber
出版情報: Paris : Springer-Verlag France, Paris, 2006
シリーズ名: Statistique et probabilités appliquées ;
オンライン: http://dx.doi.org/10.1007/978-2-287-34073-4
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18. Compstat 2006 - Proceedings in Computational Statistics : 17th Symposium Held in Rome, Italy, 2006
edited by Alfredo Rizzi, Maurizio Vichi
出版情報: Heidelberg : Physica-Verlag Heidelberg, 2006
オンライン: http://dx.doi.org/10.1007/978-3-7908-1709-6
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19. Cluster Analysis for Data Mining and System Identification
by János Abonyi, Balázs Feil
出版情報: Basel : Birkhäuser Verlag AG, 2007
オンライン: http://dx.doi.org/10.1007/978-3-7643-7988-9
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20. Applied Multiple Imputation : Advantages, Pitfalls, New Developments and Applications in R. 1st ed. 2020
by Kristian Kleinke, Jost Reinecke, Daniel Salfrán, Martin Spiess
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
シリーズ名: Statistics for Social and Behavioral Sciences ;
オンライン: https://doi.org/10.1007/978-3-030-38164-6
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目次情報: 続きを見る
1 Introduction and Basic Concepts
2 Missing Data Mechanism and Ignorability
3 Missing Data Methods
4 Multiple Imputation: Theory
5 Multiple Imputation: Application
6 Multiple Imputation: New Developments
A Appendices
Index
1 Introduction and Basic Concepts
2 Missing Data Mechanism and Ignorability
3 Missing Data Methods
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21. Functional and High-Dimensional Statistics and Related Fields. 1st ed. 2020
edited by Germán Aneiros, Ivana Horová, Marie Hušková, Philippe Vieu
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
シリーズ名: Contributions to Statistics ;
オンライン: https://doi.org/10.1007/978-3-030-47756-1
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Preface
List of Contributors
1 An introduction to the (postponed) 5th edition of the International Workshop on Functional and Operatorial Statistics
2 Analysis of Telecom Italia Mobile Phone Data by Space-time Regression with Differential Regularization
3 Some Numerical Test on the Convergence Rates of Regression with Differential Regularization
4 Learning with Signatures
5 About the Complexity Function in Small-ball Probability Factorization
6 Principal Components Analysis of a Cyclostationary Random Function
7 Level Set and Density Estimation on Manifolds
8 Pseudo-metrics as Interesting Tool in Nonparametric Functional Regression
9 Testing a Specification Form in Single Functional Index Model
10 A New Method for Ordering Functional Data and its Application to Diagnostic Test
11 A Functional Data Analysis Approach to the Estimation of Densities over Complex Regions
12 A Conformal Approach for Distribution-free Prediction of Functional Data
13 G-Lasso Network Analysis for Functional Data
14 Modelling Functional Data with High-dimensional Error Structure
15 Goodness-of-fit Tests for Functional Linear Models Based on Integrated Projections
16 From High-dimensional to Functional Data: Stringing Via Manifold Learning
17 Functional Two-sample Tests Based on Empirical Characteristic Functionals
18 Some Remarks on the Nelson–Siegel Model
19 Modeling the Effect of Recurrent Events on Time-to-event Processes by Means of Functional Data
20 On Robust Training of Regression Neural Networks
21 Simultaneous Inference for Function-valued Parameters: a Fast and Fair Approach
22 Single Functional Index Model under Responses MAR and Dependent Observations
23 O2S2 for the Geodata Deluge
24 Riemannian Distances between Covariance Operators and Gaussian Processes
25 Depth in Infinite-dimensional Spaces
26 Variable Selection in Semiparametric Bi-functional Models
27 Local Inference for Functional Data Controlling the Functional False Discovery Rate
28 Optimum Scale Selection for 3D Point Cloud Classification through Distance Correlation
29 Generalized Functional Partially Linear Single-index Models
30 Functional Outlier Detection through Probabilistic Modelling
31 Topological Object Data Analysis Methods with an Application to Medical Imaging
32 Distribution-free Pointwise Adjusted %-values for Functional Hypotheses
Authors Index
Preface
List of Contributors
1 An introduction to the (postponed) 5th edition of the International Workshop on Functional and Operatorial Statistics
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22. Nonparametric Statistics : 4th ISNPS, Salerno, Italy, June 2018. 1st ed. 2020
edited by Michele La Rocca, Brunero Liseo, Luigi Salmaso
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
シリーズ名: Springer Proceedings in Mathematics & Statistics ; 339
オンライン: https://doi.org/10.1007/978-3-030-57306-5
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Preface
Portfolio optimisation via graphical least squares estimation (Saeed Aldahmani, Hongsheng Dai, Qiao-Zhen Zhang and Marialuisa Restaino)
Change of Measure Applications in Nonparametric Statistics (Mayer Alvo)
Choosing between weekly and monthly volatility drivers within a Double Asymmetric GARCH-MIDAS model (Alessandra Amendola, Vincenzo Candila and Giampiero M. Gallo)
Goodness-of-fit test for the baseline hazard rate (Anfriani, A. and Butucea, C. and Gerardin E. and Jeantheau, T. and Lecleire U.)
Permutation tests for multivariate stratified data: synchronized or unsynchronized permutations? (Rosa Arboretti, Eleonora Carrozzo and Luigi Salmaso)
An extension of the dgLARS method to high-dimensional relative risk regression models (Luigi Augugliaro, Ernst C. Wit and Angelo M. Mineo)
A kernel goodness-of-fit test for maximum likelihood density estimates of normal mixtures. (Dimitrios Bagkavos and Prakash N. Patil)- Robust estimation of sparse signal with unknown sparsity cluster value (Eduard Belitser, Nurzhan Nurushev, and Paulo Serra)
Test for sign effect in intertemporal choice experiments: a nonparametric solution (Stefano Bonnini and Isabel Maria Parra Oller)
Nonparametric first-order analysis of spatial and spatio-temporal point processes (M.I. Borrajo, I. Fuentes-Santos and W. González-Manteiga)
Bayesian nonparametric prediction with multi-sample data (Federico Camerlenghi, Antonio Lijoi and Igor Prünster)
Algorithm for Automatic Description of Historical Series of Forecast Error in Electrical Power Grid (Gaia Ceresa, Andrea Pitto, Diego Cirio and Nicolas Omont)
Linear wavelet estimation in regression with additive and multiplicative noise (Christophe Chesneau, Junke Kou and Fabien Navarro)
Speeding up algebraic-based sampling via permutations (Francesca Romana Crucinio and Roberto Fontana)
Obstacle Problems For Nonlocal Operators: A Brief Overview (Donatella Danielli, Arshak Petrosyan, and Camelia A. Pop)
Low and high resonance components restoration in multichannel data (Daniela De Canditiis and Italia De Feis)
Kernel circular deconvolution density estimation (Marco Di Marzio, Stefania Fensore, Agnese Panzera, Charles C. Taylor)
Asymptotic for Relative Frequency when Population is Driven by Arbitrary Unknown Evolution (Silvano Fiorin)
Semantic keywords clustering to optimize Text Ads campaigns (Pietro Fodra, Emmanuel Pasquet, Guillaume Mohr, Bruno Goutorbe, and Matthieu Cornec)
A Note on Robust Estimation of the Extremal Index (M. Ivette Gomes, Cristina Miranda and Manuela Souto de Miranda)
Multivariate permutation tests for ordered categorical data (Huiting Huang, Fortunato Pesarin, Rosa Arboretti, Riccardo Ceccato)
Smooth nonparametric survival analysis (Dimitrios Ioannides and Dimitrios Bagkavos)
Density estimation using multiscale local polynomial transforms (Maarten Jansen)
On Sensitivity of Metalearning: An Illustrative Study for Robust Regression (Jan Kalina)
Function-parametric empirical processes, projections and unitary operators (Estáte Khmaladze)
Rank-based Analysis of Multivariate Data in Factorial Designs and Its Implementation in R (Maximilian Kiefel and Arne C. Bathke)
Tests for Independence Involving Spherical Data (Pierre Lafaye de Micheaux, Simos Meintanis and Thomas Verdebout)
Interval-Wise Testing of Functional Data Defined on Two-dimensional Domains(Patrick B. Langthaler, Alessia Pini and Arne C. Bathke)
Assessing Data Support for the Simplifying Assumption in Bivariate Conditional Copulas (Evgeny Levi and Radu V. Craiu)
Semiparametric weighting estimations of a zero-inflated Poisson regression with missing in covariates (Lukusa, M.T. and Phoa, F.K.H.)
The Discrepancy Method for Extremal Index Estimation (Natalia Markovich)
Correction for optimisation bias in structured sparse high-dimensional variable selection (Bastien Marquis and Maarten Jansen)
United Statistical Algorithms and Data Science: An Introduction To The Principles (Subhadeep Mukhopadhyay)
The Halfspace Depth Characterization Problem (Stanislav Nagy)
A component multiplicative error model for realized volatility measures (Antonio Naimoli and Giuseppe Storti)
Asymptotically distribution-free goodness-of-fit tests for testing independence in contingency tables of large dimensions (Thuong T. M. Nguyen)
Incorporating model uncertainty in the construction of bootstrap prediction intervals for functional time series (Efstathios Paparoditis and Han Lin Shang)
Measuring and Estimating Overlap of Distributions: A comparison of approaches from various disciplines (Judith H. Parkinson and Arne C. Bathke)
Bootstrap confidence intervals for sequences of missing values in multivariate time series (Maria Lucia Parrella, Giuseppina Albano, Michele La Rocca and Cira Perna)
On Parametric Estimation of Distribution Tails (Igor Rodionov)
An empirical comparison of global and local functional depths (Carlo Sguera and Rosa E. Lillo)
AutoSpec: Detecting Exiguous Frequency Changes in Time Series (David S. Stoffer)
Bayesian quantile regression in differential equation models (Qianwen Tan and Subhashis Ghosal)
Predicting plant endemicity based on herbarium data: application to French data (Jessica Tressou, Thomas Haevermans and Liliane Bel)
Monte Carlo Permutation Tests for Assessing Spatial Dependence at Different Scales (Craig Wang and Reinhard Furrer)
Introduction to independent counterfactuals (Marcin Wolski)
The Potential for Nonparametric Joint Latent Class Modeling of Longitudinal and Time-to-Event Data (Ningshan Zhang and Jeffrey S. Simonoff)
To Rank or to Permute when Comparing an Ordinal Outcome Between Two Groups While Adjusting for a Covariate? (Georg Zimmermann)
Preface
Portfolio optimisation via graphical least squares estimation (Saeed Aldahmani, Hongsheng Dai, Qiao-Zhen Zhang and Marialuisa Restaino)
Change of Measure Applications in Nonparametric Statistics (Mayer Alvo)
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23. Excel 2019 for Biological and Life Sciences Statistics : A Guide to Solving Practical Problems. 2nd ed. 2020
by Thomas J. Quirk, Meghan H. Quirk, Howard F. Horton
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
シリーズ名: Excel for Statistics ;
オンライン: https://doi.org/10.1007/978-3-030-39281-9
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目次情報: 続きを見る
Preface
Acknowledgements
1 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean
2 Random Number Generator
3 Confidence Interval About the Mean Using the TINV Function and Hypothesis
4 One-Group t-Test for the Mean
5 Two-Group t-Test of the Difference of the Means for Independent Groups
6 Correlation and Simple Linear Regression
7 Multiple Correlation and Multiple Regression
8 One-Way Analysis of Variance (ANOVA)
Appendix A: Answers to End-of-Chapter Practice Problems
Appendix B: Practice Test
Appendix C: Answers to Practice Test
Appendix D: Statistical Formulas
Appendix E: t-table
Index
Preface
Acknowledgements
1 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean