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Modern Applied Statistics With S

Hawaii International Conference on System Sciences

1. Introduction 1.1 An Overview 1.2 Some Examples 1.3 A Brief History 1.4 A Chapter Summary 2. Probability 2.1 Introduction 2.2 Sample Spaces and the Algebra of Sets 2.3 The Probability Function 2.4 Conditional Probability 2.5 Independence 2.6 Combinatorics 2.7 Combinatorial Probability 2.8 Taking a Second Look at Statistics (Monte Carlo Techniques) 3. Random Variables 3.1 Introduction 3.2 Binomial and Hypergeometric Probabilities 3.3 Discrete Random Variables 3.4 Continuous Random Variables 3.5 Expected Values 3.6 The Variance 3.7 Joint Densities 3.8 Transforming and Combining Random Variables 3.9 Further Properties of the Mean and Variance 3.10 Order Statistics 3.11 Conditional Densities 3.12 Moment-Generating Functions 3.13 Taking a Second Look at Statistics (Interpreting Means) Appendix 3.A.1 MINITAB Applications 4. Special Distributions 4.1 Introduction 4.2 The Poisson Distribution 4.3 The Normal Distribution 4.4 The Geometric Distribution 4.5 The Negative Binomial Distribution 4.6 The Gamma Distribution 4.7 Taking a Second Look at Statistics (Monte Carlo Simulations) Appendix 4.A.1 MINITAB Applications Appendix 4.A.2 A Proof of the Central Limit Theorem 5. Estimation 5.1 Introduction 5.2 Estimating Parameters: The Method of Maximum Likelihood and the Method of Moments 5.3 Interval Estimation 5.4 Properties of Estimators 5.5 Minimum-Variance Estimators: The Crami?½r-Rao Lower Bound 5.6 Sufficient Estimators 5.7 Consistency 5.8 Bayesian Estimation 5.9 Taking A Second Look at Statistics (Beyond Classical Estimation) Appendix 5.A.1 MINITAB Applications 6. Hypothesis Testing 6.1 Introduction 6.2 The Decision Rule 6.3 Testing Binomial Dataâ H0: p = po 6.4 Type I and Type II Errors 6.5 A Notion of Optimality: The Generalized Likelihood Ratio 6.6 Taking a Second Look at Statistics (Statistical Significance versus â Practicalâ Significance) 7. Inferences Based on the Normal Distribution 7.1 Introduction 7.2 Comparing Y-i?½ s/ vn and Y-i?½ S/ vn 7.3 Deriving the Distribution of Y-i?½ S/ vn 7.4 Drawing Inferences About i?½ 7.5 Drawing Inferences About s2 7.6 Taking a Second Look at Statistics (Type II Error) Appendix 7.A.1 MINITAB Applications Appendix 7.A.2 Some Distribution Results for Y and S2 Appendix 7.A.3 A Proof that the One-Sample t Test is a GLRT Appendix 7.A.4 A Proof of Theorem 7.5.2 8. Types of Data: A Brief Overview 8.1 Introduction 8.2 Classifying Data 8.3 Taking a Second Look at Statistics (Samples Are Not â Validâ !) 9. Two-Sample Inferences 9.1 Introduction 9.2 Testing H0: i?½X =i?½Y 9.3 Testing H0: s2X=s2Yâ The F Test 9.4 Binomial Data: Testing H0: pX = pY 9.5 Confidence Intervals for the Two-Sample Problem 9.6 Taking a Second Look at Statistics (Choosing Samples) Appendix 9.A.1 A Derivation of the Two-Sample t Test (A Proof of Theorem 9.2.2) Appendix 9.A.2 MINITAB Applications 10. Goodness-of-Fit Tests 10.1 Introduction 10.2 The Multinomial Distribution 10.3 Goodness-of-Fit Tests: All Parameters Known 10.4 Goodness-of-Fit Tests: Parameters Unknown 10.5 Contingency Tables 10.6 Taking a Second Look at Statistics (Outliers) Appendix 10.A.1 MINITAB Applications 11. Regression 11.1 Introduction 11.2 The Method of Least Squares 11.3 The Linear Model 11.4 Covariance and Correlation 11.5 The Bivariate Normal Distribution 11.6 Taking a Second Look at Statistics (How Not to Interpret the Sample Correlation Coefficient) Appendix 11.A.1 MINITAB Applications Appendix 11.A.2 A Proof of Theorem 11.3.3 12. The Analysis of Variance 12.1 Introduction 12.2 The F Test 12.3 Multiple Comparisons: Tukeyâ s Method 12.4 Testing Subhypotheses with Contrasts 12.5 Data Transformations 12.6 Taking a Second Look at Statistics (Putting the Subject of Statistics togetherâ the Contributions of Ronald A. Fisher) Appendix 12.A.1 MINITAB Applications Appendix 12.A.2 A Proof of Theorem 12.2.2 Appendix 12.A.3 The Distribution of SSTR/(kâ 1) SSE/(nâ k)When H1 is True 13. Randomized Block Designs 13.1 Introduction 13.2 The F Test for a Randomized Block Design 13.3 The Paired t Test 13.4 Taking a Second Look at Statistics (Choosing between a Two-Sample t Test and a Paired t Test) Appendix 13.A.1 MINITAB Applications 14. Nonparametric Statistics 14.1 Introduction 14.2 The Sign Test 14.3 Wilcoxon Tests 14.4 The Kruskal-Wallis Test 14.5 The Friedman Test 14.6 Testing for Randomness 14.7 Taking a Second Look at Statistics (Comparing Parametric and Nonparametric Procedures) Appendix 14.A.1 MINITAB Applications Appendix: Statistical Tables Answers to Selected Odd-Numbered Questions Bibliography Index

http://library.um.ac.id/free-contents/downloadpdf.php/buku/an-introduction-to-mathematical-statistics-and-its-applications-richard-j-larsen-morris-l-marx-12385.pdf

An introduction to mathematical statistical and its applications / Richard J. Larsen, Morris L. Marx

We present a realistic, yet computationally inexpensive simulation model for IEEE 802.11p radio shadowing in urban environments. Based on real world measurements using IEEE 802.11p/DSRC devices, we estimated the effect that buildings and other obstacles have on the radio communication between vehicles. Especially for evaluating safety applications in the field of Vehicular Ad Hoc Networks (VANETs), stochastic models are not sufficient for evaluating the radio communication in simulation. Motivated by similar work on WiFi measurements, we therefore created an empirical model for modeling buildings and their properties to accurately simulate the signal propagation. We validated our model using real world measurements in a city scenario for different types of obstacles. Our simulation results show a very high accuracy when compared with the measurement results, while only requiring a marginal overhead in terms of computational complexity.

/pdf/a-computationally-inexpensive-empirical-model-of-ieee-802-1l4rf8i4sb.pdf

A computationally inexpensive empirical model of IEEE 802.11p radio shadowing in urban environments

Welcome to the second installment of IJBDCN. This issue contains three research papers and a comprehensive survey article on mobile ad hoc networks. We would like to publish a couple of survey or tutorial articles per year as we believe this to be of value to our readers. Many research papers are necessarily focused and do not allow for a " panoramic " view of a particular subject. This is the gap that well-written survey or tutorial papers can fill. We are also planning a guest-edited special issue for the last quarter of this year and welcome your suggestions for future special issues of the journal. This second issue starts with a paper entitled " An Approach to Solving the Surviv-able Capacitated Network Design Problem " where Sridhar and Park studied the problem of selecting links of a network to construct primary and secondary routes for transfer of commodity traffic between nodes of the network. Their technique allows the design of survivable and cost-effective networks. In the second paper, " Query Processing Strategies for Location-Dependent Information Services " , Jayaputera and Taniar propose a new approach to generate a query result for location-dependent information services (LDIS). They argue that choosing a square as the scope of a query and dividing it into four equal regions, where a user is a center point of the scope, results in a faster searching time to find targets queried and brings a bigger chance to get rare targets. In addition, by avoiding resubmitting the same queries when the query results missed, the approach reduced bandwidth use at both the server and client sides. The third paper, " Addressing SPAM E-Mail Using Hashcash " by Curran and Honan tackles a problem experienced by most of us. The authors present the Hashcash proof-of-work approach and investigate the feasibility of implementing a solution based on that mechanism along with what they called a " cocktail " of antispam measures designed to keep junk mail under control. Finally , in the last paper, entitled " MANET: Applications, Issues, and Challenges for the Future " , Dhar presents an informative survey of mobile ad hoc networks, describing the main characteristics of those networks and how they are being used, and discussing the most pressing issues and challenges associated with these temporary wireless networks. We hope that you enjoy this and the upcoming issues of IJBDCN. Our goal is to …

International Journal of Business Data Communications and Networking

The tutorial is about traffic self-similarity. It is a review of basic concepts in traffic self-similarity. It is about definitions of self-similarity, key properties, measurements, models, generation of synthetic traces, revealing of specific properties in self-similar traffic, origins as well as performance impacts

Traffic Self-Similarity

The paper reports on recent developments and challenges in reliable multicast communication, with special focus on reliable multicast communication at the application layer. The foundation of reliable multicast communication is given by several components, which are multicast communication, congestion control and error control. Our paper is providing a survey of these mechanisms in multicast environments.

/pdf/a-survey-of-reliable-multicast-communication-1nprzxmtbz.pdf

A Survey of Reliable Multicast Communication

The paper reports on a modeling and evaluation study of session characteristics of BitTorrent traffic BitTorrent is a second generation Peer-to-Peer (P2P) application recently developed as an alternative to the classical client-server model to reduce the load burden on content servers and networks Results are reported on measuring, modeling and analysis of application layer traces collected at the Blekinge Institute of Technology (BIT) and a local ISP For doing this, a dedicated measurement infrastructure has been developed at BIT to collect P2P traffic A dedicated modeling methodology has been put forth as well New results are reported on session characteristics of BitTorrent, and it is observed that session interarrivals can be accurately modeled by the hyper-exponential distribution while session durations and sizes can be reasonably well modeled by the lognormal distribution

BitTorrent Session Characteristics and Models

The usage of Internet is rapidly increasing and a large part of the Internet traffic is generated by the World Wide Web (WWW) and the associated protocol HyperText Transfer Protocol (HTTP). Several important parameters that affect the performance of the WWW are bandwidth, scalability, and latency. To tackle these parameters and to improve the overall performance of the system, it is important to understand and to characterize the application level characteristics. This article is reporting on the measurement and analysis of HTTP traffic collected on the student access network at the Blekinge Institute of Technology in Karlskrona, Sweden. The analysis is done on various HTTP traffic parameters, e.g., inter-session timings, inter-arrival timings, request message sizes, response code, and number of transactions. The reported results can be useful for building synthetic workloads for simulation and benchmarking purposes.

/pdf/measurement-and-analysis-of-http-traffic-4p9vmu6n0q.pdf

Measurement and Analysis of HTTP Traffic

The main goals of the paper are towards an understanding of the delay process in best-effort Internet for both non-congested and congested networks. A dedicated measurement system is re-ported for ...

/pdf/delay-performance-in-ip-routers-36o990uzhe.pdf

Adrian Popescu

Papers

Traffic Self-Similarity

A Survey of Reliable Multicast Communication

BitTorrent Session Characteristics and Models

Measurement and Analysis of HTTP Traffic

Delay Performance in IP Routers