Suchergebnisse

Cover -- Half Title -- Title -- Copyright -- Content -- Preface To The Second Edition -- Preface -- Chapter 1. INTRODUCTION -- 1.1 Samples Versus Populations -- 1.2 Software -- 1.3 R Basics -- 1.3.1 Entering Data -- 1.3.2 R Functions And Packages -- 1.3.3 Data Sets -- 1.3.4 Arithmetic Operations -- Chapter 2. NUMERICAL AND GRAPHICAL SUMMARIES OF DATA -- 2.1 Basic Summation Notation -- 2.2 Measures Of Location -- 2.2.1 The Sample Mean -- 2.2.2 R Function Mean -- 2.2.3 The Sample Median -- 2.2.4 R Function For The Median -- 2.3 A Criticism Of The Median: It Might Trim Too Many Values -- 2.3.1 R Function For The Trimmed Mean -- 2.3.2 A Winsorized Mean -- 2.3.3 R Function Winmean -- 2.3.4 What Is A Measure Of Location -- 2.4 Measures Of Variation Or Scale -- 2.4.1 Sample Variance And Standard Deviation -- 2.4.2 R Functions Var And Sd -- 2.4.3 The Interquartile Range -- 2.4.4 R Functions Idealf And Ideafiqr -- 2.4.5 Winsorized Variance -- 2.4.6 R Function Winvar -- 2.4.7 Median Absolute Deviation -- 2.4.8 R Function Mad -- 2.4.9 Average Absolute Distance From The Median -- 2.4.10 Other Robust Measures of Variation -- 2.4.11 R Functions bivar, pbvar, tauvar, and tbs -- 2.5 DETECTING OUTLIERS -- 2.5.1 A Method Based on the Mean and Variance -- 2.5.2 A Better Outlier Detection Rule: The MAD-Median Rule -- 2.5.3 R Function out -- 2.5.4 The Boxplot -- 2.5.5 R Function boxplot -- 2.5.6 Modifications of the Boxplot Rule for Detecting Outliers -- 2.5.7 R Function outbox -- 2.5.8 Other Measures of Location -- 2.5.9 R Functions mom and onestep -- 2.6 HISTOGRAMS -- 2.6.1 R Functions hist and splot -- 2.7 KERNEL DENSITY ESTIMATORS -- 2.7.1 R Functions kdplot and akerd -- 2.8 STEM-AND-LEAF DISPLAYS -- 2.8.1 R Function stem -- 2.9 SKEWNESS -- 2.9.1 Transforming Data -- 2.10 CHOOSING A MEASURE OF LOCATION -- 2.11 EXERCISES