Cargando…
Introduction to Statistics Through Resampling Methods and R.
Written in an informal, highly accessible style, this text is an excellent guide to descriptive statistics, estimation, testing hypotheses, and model building. It includes all the tools needed to facilitate quick learning, including: more than 250 exercises with selected hints, multiple explanations...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York :
Wiley,
2012.
|
| Edición: | 2nd ed. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover; Title page; Copyright page; Contents; Preface; Chapter 1: Variation; 1.1 Variation; 1.2 Collecting Data; 1.2.1 A Worked-Through Example; 1.3 Summarizing Your Data; 1.3.1 Learning to Use R; 1.4 Reporting Your Results; 1.4.1 Picturing Data; 1.4.2 Better Graphics; 1.5 Types of Data; 1.5.1 Depicting Categorical Data; 1.6 Displaying Multiple Variables; 1.6.1 Entering Multiple Variables; 1.6.2 From Observations to Questions; 1.7 Measures of Location; 1.7.1 Which Measure of Location?; *1.7.2 The Geometric Mean; 1.7.3 Estimating Precision; 1.7.4 Estimating with the Bootstrap
- 1.8 Samples and Populations1.8.1 Drawing a Random Sample; *1.8.2 Using Data That Are Already in Spreadsheet Form; 1.8.3 Ensuring the Sample Is Representative; 1.9 Summary and Review; Chapter 2: Probability; 2.1 Probability; 2.1.1 Events and Outcomes; 2.1.2 Venn Diagrams; 2.2 Binomial Trials; 2.2.1 Permutations and Rearrangements; *2.2.2 Programming Your Own Functions in R; 2.2.3 Back to the Binomial; 2.2.4 The Problem Jury; *2.3 Conditional Probability; 2.3.1 Market Basket Analysis; 2.3.2 Negative Results; 2.4 Independence; 2.5 Applications to Genetics; 2.6 Summary and Review
- Chapter 3: Two Naturally Occurring Probability Distributions3.1 Distribution of Values; 3.1.1 Cumulative Distribution Function; 3.1.2 Empirical Distribution Function; 3.2 Discrete Distributions; 3.3 The Binomial Distribution; *3.3.1 Expected Number of Successes in n Binomial Trials; 3.3.2 Properties of the Binomial; 3.4 Measuring Population Dispersion and Sample Precision; 3.5 Poisson: Events Rare in Time and Space; 3.5.1 Applying the Poisson; 3.5.2 Comparing Empirical and Theoretical Poisson Distributions; 3.5.3 Comparing Two Poisson Processes; 3.6 Continuous Distributions
- 3.6.1 The Exponential Distribution3.7 Summary and Review; Chapter 4: Estimation and the Normal Distribution; 4.1 Point Estimates; 4.2 Properties of the Normal Distribution; 4.2.1 Student's t-Distribution; 4.2.2 Mixtures of Normal Distributions; 4.3 Using Confidence Intervals to Test Hypotheses; 4.3.1 Should We Have Used the Bootstrap?; 4.3.2 The Bias-Corrected and Accelerated Nonparametric Bootstrap; 4.3.3 The Parametric Bootstrap; 4.4 Properties of Independent Observations; 4.5 Summary and Review; Chapter 5: Testing Hypotheses; 5.1 Testing a Hypothesis; 5.1.1 Analyzing the Experiment
- 5.1.2 Two Types of Errors5.2 Estimating Effect Size; 5.2.1 Effect Size and Correlation; 5.2.2 Using Confidence Intervals to Test Hypotheses; 5.3 Applying the t-Test to Measurements; 5.3.1 Two-Sample Comparison; 5.3.2 Paired t-Test; 5.4 Comparing Two Samples; 5.4.1 What Should We Measure?; 5.4.2 Permutation Monte Carlo; 5.4.3 One- vs. Two-Sided Tests; 5.4.4 Bias-Corrected Nonparametric Bootstrap; 5.5 Which Test Should We Use?; 5.5.1 p-Values and Significance Levels; 5.5.2 Test Assumptions; 5.5.3 Robustness; 5.5.4 Power of a Test Procedure; 5.6 Summary and Review