Yates, D.S. et al.
The Practice of Statistics 3rd ed.
Ti-83/84/89 Graphing Calculator Enhanced
W.H. Freeman, USA 2006.12
926 pp.(H)
ISBN 0-7167-7309-0
16,000円
Contents
Part.1. Analyzing Data:Looking for Patterns and Departures From Patterns: 1. Exploring Data/ 2. Describing Location in a Distribution/ 3. Examining Relationships/ 4. More about Relationships between Two Variables/ Part.2. Producing Data:Surveys,Observational Studies,and Experiments: 5. Producing Data/ Part.3.Probability and Random Variables:Foundations for Inference: 6. Probability and Simulation: The Study of Randomness/ 7. Random Variables/ 8. The Binomial and Geometric Distributions/ 9. Sampling Distributions/ Part.4.Inference:Conclusions with Confidence: 10. Estimationg with Confidence/ 11. Testing a Claim/ 12. Significance Tests in Practice/ 13. Comparing Two Population Parameters/ 14. inference for Distributions of Categorical Variables:Chi-Square Procedures/ 15.Inference for Regression/ Solutions to Odd-Numbered Exercises/ Notes and Data Sources/ Photo Credits/ index/ Tables: Table A. Standard Normal Probabilities/ Table B. Random digits/ Table C. t distribution critical values/ Table D. Chi-square distribution critical values/ *
Stapleton , J. H.
Models for Probability and Statistical Inference
Theory and Applications
（確率と統計推論モデル）
John Wiley & Sons 2007.12
440 pp.(H)
ISBN 0-470-07372-1
14,400円
Contents
part.1. Probability Models: 1.1 Discrete Probability Models/ 1.2 Conditional Probability and Independence/ 1.3 Random Variables/ 1.4 Expectation/ 1.5 The Variance/ 1.6 Covariance and Correlation/ part.2. Special Discrete Distributions: 2.1 The Binomial Distribution/ 2.2 The Hypergeometric Distribution/ 2.3 The Geometric and Negative Binomial Distributions/ 2.4 The Poisson Distribution/ part.3. Continuous Random Variables:3.1 Continuous RV's and Their Distributions/ 3.2 Expected Values and Variances/ 3.3 Transformations of Random Variables/ 3.4Joint Densities/ part.4 Special Continuous Distributions: 4.1 The Normal Distribution/ 4.2 The Gamma Distribution/ part.5. Conditional Distributions: 5.1 The Discrete Case/ 5.2 Conditional Expectations for the Discrete Case/ 5.3 Conditional Densities and Expectations for Continuous RV's/ part.6. Limit Laws:6.1 Moment Generating Functions/ 6.2 Convergence in Probability and in Distribution/ 6.3 The Central Limit Theorem/ 6.4 The Delta-Method/ part.7. Estimation: 7.1 Point Estimation/ 7.2 The Method of Moments/ 7.3 Maximum Likelihood/ 7.4 Consistency/ 7.5 The Ω-Method/ 7.6 Confidence Intervals/ 7.7 Fisher Information, The Cramer-Rao Bound, and Asymptotic Normality of MLE's/ 7.8 Sufficiency/ part.8. Testing Hypotheses: 8.1 Introduction/ 8.2 The Neyman-Pearson Lemma/ 8.3 The Likelihood Ratio Test/ 8.4 The p-Value and the Relationship Between Tests of Hypotheses and Confidence Intervals/ part.9. The Multivariate Normal, Chi-square, t, and F-Distributions: 9.1 The Multivariate Normal Distribution/ 9.2 The Central and Noncentral Chi-Square Distributions/ 9.3 Student's t-Distribution/ 9.4 The F-Distribution/ part.10. Nonparametric Statistics:10.1 The Wilcoxon Test and Estimator/ 10.2 One Sample Methods/ 10.3 The Kolmogorov-Smirnov Tests/ part.11. Linear Models: 11.1 The Principle of Least Squares/ 11.2 Linear Models/ 11.3 F-Tests for H0/ 11.4 Two-Way Analysis of Variance./ part.12. Frequency Data:12.1 Logistic Regression/ 12.2 Two-Way Frequency Tables/ 12.3 Chi-Square Goodness of Fit Tests/ part.13. Miscellaneous Topics: 13.1 Survival Analysis/ 13.2 Bootstrapping/ 13.3 Bayesian Statistics/ 13.4 Sampling/
* This textbook is an introduction to probability and statistical inference for students. It contains a large amount of figures, with simulations and graphs, produced by the statistical package S-Plus(r), included throughout.
* It discusses methods for the computer simulation of observations from specified distributions and provides flexibility for instructors. Each section is followed by a range of problems, from simple to more complex with selected answers. *
Hardle, W. & Simar, L.
Applied Multivariate Statistical Analysis 2nd ed.
Springer-Verlag 2007.
458 pp.(P)
ISBN 3-540-72243-2
13,100円
Contents
Part.I: Descriptive Techniques : 1. Comparison of Batches/ Part.II: Multivariate Random Variables : 2. A Short Excursion into Matrix Algebra/ 3. Moving to Higher Dimensions/ 4. Multivariate Distributions/ 5. Theory of the Multinormal/ 6. Theory of Estimation/ 7. Hypothesis Testing/ Part.III: Multivariate Techniques: 8. Decomposition of Data Matrices by Factors/ 9. Principal Components Analysis/ 10. Factor Analysis/ 11. Cluster Analysis/ 12. Discriminant Analysis/ 13. Correspondence Analysis/ 14. Canonical Correlation Analysis/ 15 Multidimensional Scaling/ 16 Conjoint Measurement Analysis/ 17 Applications in Finance/ 18 Computationally Intensive Techniques/ A. Symbols and Notations/ B. Data: B.1 Boston Housing Data/ B.2 Swiss Bank Notes/ B.3 Car Data/ B.4 Classic Blue Pullovers Data/ B.5 U.S. Companies Data/ B.6 French Food Data / B.7 CarMarks/ B.8 French Baccalaurｫeat Frequencies/ B.9 Journaux Data/ B.10 U.S. Crime Data/ B.11 Plasma Data/ B.12WAIS Data/ B.13ANOVA Data/ B.14 Timebudget Data/ B.15Geopol Data/ B.16 U.S. Health Data/ B.17 Vocabulary Data/ B.18Athletic Records Data/ B.19 Unemployment Data/ B.20 Annual Population Data/ B.21 Bankruptcy Data/ Bibliography/ Index/
* A key advantage of the work is its accessibility. This is because, in its focus on applications, the book presents the tools and concepts of multivariate data analysis in a way that is understandable for non-mathematicians and practitioners who need to analyze statistical data. In this second edition a wider scope of methods and applications of multivariate statistical analysis is introduced. All quantlets have been translated into the R and Matlab language and are made available online. *
Kirchgassner, G. & Wolters, J.
Introduction to Modern Time Series Analysis
Springer-Verlag 2007.
274 pp.(H)
ISBN 3-540-73290-X
16,400円
Contents
Part.1: Introduction and Basics: 1.1 The Historical Development of Time Series Analysis/ 1.2 Graphical Representations of Economic Time Series/ 1.3 Ergodicity and Stationarity/ 1.4 The Wold Decomposition/ References/ Part.2: 2 Univariate Stationary Processes: 2.1 Autoregressive Processes/ 2.2 Moving Average Processes/ 2.3 Mixed Processes/ 2.4 Forecasting/ 2.5 The Relation between Econometric Models and ARMA Processes/ References/ Part.3: Granger Causality: 3.1 The Definition of Granger Causality/ 3.2 Characterisations of Causal Relations in Bivariate Models/ 3.3 Causality Tests/ 3.4 Applying Causality Tests in a Multivariate Setting/ 3.5 Concluding Remarks/ References/ Part.4: Vector Autoregressive Processes: 4.1 Representation of the System/ 4.2 Granger Causality/ 4.3 Impulse Response Analysis/ 4.4 Variance Decomposition/ 4.5 Concluding Remarks/ References/ Part.5: Nonstationary Processes: 5.1 Forms of Nonstationarity/ 5.2 Trend Elimination/ 5.3 Unit Root Tests/ 5.4 Decomposition of Time Series/ 5.5 Further Developments/ 5.6 Deterministic versus Stochastic Trends in Economic Time Series/ References/ Part.6: Cointegration: 6.1 Definition and Properties of Cointegrated Processes/ 6.2 Cointegration in Single Equation Models: Representation, Estimation and Testing/ 6.3 Cointegration in Vector Autoregressive Models/ 6.4 Cointegration and Economic Theory/ References/ Part.7: Autoregressive Conditional Heteroskedasticity: 7.1 ARCH Models/ 7.2 Generalised ARCH Models/ 7.3 Estimation and Testing/ 7.4 ARCH/GARCH Models as Instruments of Financial Market Analysis/ References/ Index of Names and Authors/ Subject Index/
* This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series. It bridges the gap between methods and realistic applications. This book contains the most important approaches to analyze time series which may be stationary or nonstationary. It starts with modeling and forecasting univariate time series and then presents Granger causality tests and vector autoregressive models for multiple stationary time series. *
Kowalski, J. & Tu, X. M.
Modern Applied U-Statistics
現代応用U統計学
John Wiley & Sons 2007.12
378 pp.(H)
ISBN 0-471-68227-6
13,200円
Contents
* Built on years of collaborative research and academic experience, Modern Applied U-Statistics successfully presents a thorough introduction to the theory of U-statistics using in-depth examples and applications that address contemporary areas of study including biomedical and psychosocial research. Utilizing a "learn by example" approach, this book provides an accessible, yet in-depth, treatment of U-statistics, as well as addresses key concepts in asymptotic theory by integrating translational and cross-disciplinary research.
* The authors begin with an introduction of the essential and theoretical foundations of U-statistics such as the notion of convergence in probability and distribution, basic convergence results, stochastic Os, inference theory, generalized estimating equations, as well as the definition and asymptotic properties of U-statistics. *
Finkenstadt, B. et al. ed.
Statistical Methods of Spatio-Temporal Systems
Chapman & Hall/ CRC 2007.
286 pp. (H)
ISBN 1-58488-593-9
12,000円
Contents
1.Spatio-Temporal Point Processes: Methods and Applications/ 2.Spatio-Temporal Modelling - with a View to Biological Growth/ 3.Using Transforms to Analyze Space-Time Processes/ 4.Geostatistical Space-Time Models, Stationarity, Separability and Full Symmetry/ 5.Space-Time Modelling of Rainfall for Continuous Simulation/ 6.A Primer on Space-Time Modelling from a Bayesian Perspective/ Index/ *
Peck, R.
Introduction to Statistics and Data Analysis 3rd ed.
Duxbury Pr., USA 2007.3
888 pp.
ISBN 0-495-11873-7
20,200円
Contents
1.The Role of Statistics and the Data Analysis Process/ 2.Collecting Data Sensibly/ 3.Graphical Methods for Describing Data/ 4.Numerical Methods for Describing Data/ 5.Summarizing Bivariate Data/ 6.Probability/ 7.Random Variables and Probability Distributions/ 8.Sampling Variability and Sampling Distributions/ 9.Estimation Using a Single Sample/ 10.Hypothesis Testing Using a Single Sample/ 11.Comparing Two Populations of Treatments/ 12.The Analysis of Categorical Data and Goodness-of-Fit Tests/ 13.Simple Linear Regression and Correlation:Inferential Methods/ 14.Multiple Regression Analysis/ 15.Analysis of Variance/ 16.Nonparametric (Distribution-Free) Statistical Methods/ Appendix A:Statistical Tables/ Appendix B:References/ Answers to Selected Odd-Numbered Exercises/ Index/ *
Baltagi, B. H.
Econometrics 4th ed.
Springer-Verlag 2008.2
392 pp.(P)
ISBN 3-540-76515-8
8,200円
Contents
Part I: 1. What Is Econometrics?/ 2. Basic Statistical Concepts/ 3. Simple Linear Regression/ 4. Multiple Regression Analysis/ 5. Violations of the Classical Assumptions/ 6. Distributed Lags and Dynamic Models/ Part II: 7. The General Linear Model: The Basics/ 8. Regression Diagnostics and Specification Tests/ 9. Generalized Least Squares/ 10. Seemingly Unrelated Regressions/ 11. Simultaneous Equations Model/ 12. Pooling Time-Series of Cross-Section Data/ 13. Limited Dependent Variables/ 14. Time-Series Analysis/ Index/
* This textbook teaches some of the basic econometric methods and the underlying assumptions behind them. It also includes a simple and concise treatment of more advanced topics in spatial correlation, panel data, limited dependent variables, regression diagnostics, specification testing and time series analysis. Some of the strengths of this book lie in presenting difficult material in a simple, yet rigorous manner. Each chapter has a set of theoretical exercises as well as an empirical illustration using a real economic application. These empirical exercises usually replicate a published article using Stata or Eviews. "Badi H. Baltagi is distinguished Professor of Economics, and Senior Research Associate at the Center for Policy Research, Syracuse University. He received his Ph.D. in Economics at the University of Pennsylvania in 1979. Before joining Syracuse University, he served on the faculty at the University of Houston and Texas A&M University. He is a fellow of the Journal of Econometrics and a recipient of the Multa and Plura Scripsit Awards from Econometric Theory." *
677-48 登録日 08.02.04
