Appendix Indices

R Code Snippets

2.1: Comparison of mean, median, trimmed and winsorized mean
2.2: Calculation of the ideal fourth

Wilcox Functions

2.1: Other dispersion measures

Formulas

Definitions

2.1 Ideal fourth
2.2 Median Absolute Deviation (MAD)
2.3 Method for detecting outliers based on the mean and the variance
2.4 The MAD-Median rule
2.5 How bloxpots declare outliers
2.6 Detecting outliers with modified boxplot rule
2.7 Detecting outliers with modified boxplot rule

Examples

2.1: The mean is still relevant
2.2: Compare different types of quantiles and IQRs
2.3: Calcuation of the Winsorized Variance
2.4: Calculation of the Median Absolute Deviation with mad
2.5: Comparison of other robust measures of variation
2.6: Demonstration data for masking of outliers
2.7: Demonstrate results of function out(x)
2.8: Demonstration of the built-in R function boxplot(x)
2.9: Outliers values with the boxplot rule using boxplot and boxplot.stats
2.10: Demonstration of the outbox function
2.11: Compare detection of outliers with different bloxplot rules
2.12: Comparing functions onestep and mom
2.13: Comparison of Histograms with hist and ggplot.
2.14: Demonstration of the r hist function with splot
2.15: Demonstration of the r hist function with ggplot2
2.16: Demonstration of the stem function

Exercises

2.1: Exercise 01
2.2: Exercise 02
2.3: Exercise 03
2.4: Exercise 04
2.5: Exercise 05
2.6: Exercise 06
2.7: Exercise 07
2.8: Exercise 08
2.9: Exercise 09
2.10: Exercise 10
2.11: Exercise 14
2.12: Exercise 15
2.13: Exercise 16
2.14: Exercise 17
2.15: Exercise 19
2.16: Exercise 20
2.17: Exercise 21
2.18: Exercise 22
2.19: Exercise 26