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“…El objetivo de este estudio es observar, describir y analizar la forma de juego tan exitosa de la acción de juego ofensivo y defensivo de los equipos Real Madrid, Inter de Milán y Chelsea, dirigidos por José Mourinho y F.C. Barcelona y Bayern München, dirigidos por Josep Guardiola. …”
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Tabla de Contenidos: “…4.7.3 Gamma GLMs for House Selling Price Data -- Appendix: GLM Analogs of Orthogonality Results for Linear Models -- Chapter Notes -- Exercises -- 5 Models for Binary Data -- 5.1 Link Functions for Binary Data -- 5.1.1 Ungrouped versus Grouped Binary Data -- 5.1.2 Latent Variable Threshold Model for Binary GLMs -- 5.1.3 Probit, Logistic, and Linear Probability Models -- 5.2 Logistic Regression: Properties and Interpretations -- 5.2.1 Interpreting : Effects on Probabilities and on Odds -- 5.2.2 Logistic Regression with Case-Control Studies -- 5.2.3 Logistic Regression is Implied by Normal Explanatory Variables -- 5.2.4 Summarizing Predictive Power: Classification Tables and ROC Curves -- 5.2.5 Summarizing Predictive Power: Correlation Measures -- 5.3 Inference About Parameters of Logistic Regression Models -- 5.3.1 Logistic Regression Likelihood Equations -- 5.3.2 Covariance Matrix of Logistic Parameter Estimators -- 5.3.3 Statistical Inference: Wald Method is Suboptimal -- 5.3.4 Conditional Logistic Regression to Eliminate Nuisance Parameters -- 5.4 Logistic Regression Model Fitting -- 5.4.1 Iterative Fitting of Logistic Regression Models -- 5.4.2 Infinite Parameter Estimates in Logistic Regression -- 5.5 Deviance and Goodness of Fit for Binary GLMS -- 5.5.1 Deviance and Pearson Goodness-of-Fit Statistics -- 5.5.2 Chi-Squared Tests of Fit and Model Comparisons -- 5.5.3 Residuals: Pearson, Deviance, and Standardized -- 5.5.4 Influence Diagnostics for Logistic Regression -- 5.6 Probit and Complementary Log-Log Models -- 5.6.1 Probit Models: Interpreting Effects -- 5.6.2 Probit Model Fitting -- 5.6.3 Log-Log and Complementary Log-Log Link Models -- 5.7 Examples: Binary Data Modeling -- 5.7.1 Example: Risk Factors for Endometrial Cancer Grade -- 5.7.2 Example: Dose-Response Study -- Chapter Notes -- Exercises -- 6 Multinomial Response Models…”

Tabla de Contenidos: “…7.5.2 The Fisher Information -- 7.6 Point Estimation -- 7.6.1 Maximum Likelihood Estimation -- 7.6.2 Method of Moments Estimator -- 7.7 Comparison of Estimators -- 7.7.1 Unbiased Estimators -- 7.7.2 Improving Unbiased Estimators -- 7.8 Confidence Intervals -- 7.9 Testing Statistical Hypotheses-The Preliminaries -- 7.10 The Neyman-Pearson Lemma -- 7.11 Uniformly Most Powerful Tests -- 7.12 Uniformly Most Powerful Unbiased Tests -- 7.12.1 Tests for the Means: One- and Two-Sample t-Test -- 7.13 Likelihood Ratio Tests -- 7.13.1 Normal Distribution: One-Sample Problems -- 7.13.2 Normal Distribution: Two-Sample Problem for the Mean -- 7.14 Behrens-Fisher Problem -- 7.15 Multiple Comparison Tests -- 7.15.1 Bonferroni's Method -- 7.15.2 Holm's Method -- 7.16 The EM Algorithm* -- 7.16.1 Introduction -- 7.16.2 The Algorithm -- 7.16.3 Introductory Applications -- 7.17 Further Reading -- 7.17.1 Early Classics -- 7.17.2 Texts from the Last 30 Years -- 7.18 Complements, Problems, and Programs -- Chapter 8 Nonparametric Inference -- 8.1 Introduction -- 8.2 Empirical Distribution Function and Its Applications -- 8.2.1 Statistical Functionals -- 8.3 The Jackknife and Bootstrap Methods -- 8.3.1 The Jackknife -- 8.3.2 The Bootstrap -- 8.3.3 Bootstrapping Simple Linear Model* -- 8.4 Non-parametric Smoothing -- 8.4.1 Histogram Smoothing -- 8.4.2 Kernel Smoothing -- 8.4.3 Nonparametric Regression Models* -- 8.5 Non-parametric Tests -- 8.5.1 The Wilcoxon Signed-Ranks Test -- 8.5.2 The Mann-Whitney test -- 8.5.3 The Siegel-Tukey Test -- 8.5.4 The Wald-Wolfowitz Run Test -- 8.5.5 The Kolmogorov-Smirnov Test -- 8.5.6 Kruskal-Wallis Test* -- 8.6 Further Reading -- 8.7 Complements, Problems, and Programs -- Chapter 9 Bayesian Inference -- 9.1 Introduction -- 9.2 Bayesian Probabilities -- 9.3 The Bayesian Paradigm for Statistical Inference…”

Tabla de Contenidos: “…8.4.1 Resampling Procedure -- 8.5 Numeric Data: ANOVA -- 8.6 Components of Variance -- 8.6.1 From ANOVA to Regression -- 8.7 Factorial Design -- 8.7.1 Stratification and Blocking -- 8.7.2 Blocking -- 8.8 The Problem of Multiple Inference -- 8.9 Continuous Testing -- 8.9.1 Medicine -- 8.9.2 Business -- 8.10 Bandit Algorithms -- 8.10.1 Web Testing -- 8.11 Appendix: ANOVA, the Factor Diagram, and the F‐Statistic -- 8.11.1 Decomposition: The Factor Diagram -- 8.11.2 Constructing the ANOVA Table -- 8.11.3 Inference Using the ANOVA Table -- 8.11.4 The F‐Distribution -- 8.11.5 Different Sized Groups -- 8.11.5.1 Resampling Method -- 8.11.5.2 Formula Method -- 8.11.6 Caveats and Assumptions -- 8.12 More than One Factor or Variable-From ANOVA to Statistical Models -- 8.13 Python: Contingency Tables and Chi‐square Test -- 8.13.1 Example: Marriage Therapy -- 8.13.2 Example: Imanishi‐Kari Data -- 8.14 Python: ANOVA -- 8.14.1 Visual Comparison of Groups -- 8.14.2 ANOVA Using Resampling Test -- 8.14.3 ANOVA Using the F‐Statistic -- Exercises -- Chapter 9 Correlation -- 9.1 Example: Delta Wire -- 9.2 Example: Cotton Dust and Lung Disease -- 9.3 The Vector Product Sum Test -- 9.3.1 Example: Baseball Payroll -- 9.3.1.1 Resampling Procedure -- 9.4 Correlation Coefficient -- 9.4.1 Inference for the Correlation Coefficient-Resampling -- 9.4.1.1 Hypothesis Test-Resampling -- 9.4.1.2 Example: Baseball Again -- 9.4.1.3 Inference for the Correlation Coefficient: Formulas -- 9.5 Correlation is not Causation -- 9.5.1 A Lurking External Cause -- 9.5.2 Coincidence -- 9.6 Other Forms of Association -- 9.7 Python: Correlation -- 9.7.1 Vector Operations -- 9.7.2 Resampling Test for Vector Product Sums -- 9.7.3 Calculating Correlation Coefficient -- 9.7.4 Calculate Correlation with numpy, pandas -- 9.7.5 Hypothesis Tests for Correlation -- 9.7.6 Using the t Statistic…”

“…Nahj al-Balāghah , the celebrated compendium of orations, letters, and sayings of Ê¿AlÄ« ibn AbÄ« á1¬Älib (d. 40/661) compiled by al-SharÄ«f al-Raá ̧ōÄ« (d. 406/1015), is a masterpiece of Arabic literature and Islamic wisdom studied and memorized avidly and continually for over a thousand years. …”

Tabla de Contenidos: “…Coexistence, migration, and integration -- 6.1 Software coexistence -- 6.2 Considerations for migration -- 6.2.1 Hardware -- 6.2.2 Direct migration -- 6.2.3 AIX -- 6.2.4 Parallel System Support Program -- 6.2.5 General Parallel File System -- 6.2.6 LoadLeveler -- 6.2.7 High-Availability Cluster Multiprocessing -- 6.3 Migration scenarios -- 6.3.1 Migrating PSSP 3.2 and AIX 4.3.3 to PSSP 3.5 and AIX 5.1 -- 6.3.2 Migrating PSSP 3.1.1 and AIX 4.3.3 to PSSP 3.5 and AIX 5.1 -- 6.3.3 Migrating PSSP 3.4 and AIX 4.3.3 to PSSP 3.5 and AIX 5.1 -- 6.3.4 Migrating PSSP 3.4 and AIX 5.1F to PSSP 3.5 and AIX 5.1F -- 6.4 Integration of SP-attached servers -- 6.4.1 pSeries 660, Model 6H1 -- 6.4.2 pSeries 690, Model 681 -- 6.4.3 S70 Enterprise Server -- 6.5 Migration tips -- Chapter 7. …”

“…That is the gift that David F einberg has brought to U CLA. I am in awe of his management skills.” …”

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