ABSTRACT
Many of the central ideas of this book are illustrated with the following simple example. Fig. 1.1 shows a sequence of 2048 successive measurements of an electrocardiogram (ECG), an electrical signal measured in millivolts and sampled 180 times per second. This example illustrates the kinds of large-magnitude “spikes” that can appear in a real data sequence, potentially obscuring other important details. This particular data sequence is available as part of the ade4 add-on package [29] for the R software environment [99]. Like Python, R is an open-source software package, developed to support a wide variety of statistical and data analysis procedures and discussed further in Sec. 1.4. The ECG dataset considered here is available as the object ecg, and the description available from the R documentation notes that the signal exhibits a variety of biologically significant components on different time scales, including a relatively long-term baseline drift due to breathing artifacts, movement artifacts, and identifiable components of the heart rhythm, including an occasional arrhythmia. The documentation also notes that this data sequence was provided by Gust Bardy and Per Reinall of the University of Washington, and it cites the book by Percival and Walden for further discussion [93].
