Download A first course in statistical programming with R by W. John Braun, Duncan J. Murdoch PDF

By W. John Braun, Duncan J. Murdoch

This is often the single advent you will need to begin programming in R, the open-source language that's loose to obtain, and allows you to adapt the resource code to your personal specifications. Co-written by means of one of many R middle improvement crew, and by way of a longtime R writer, this ebook comes with genuine R code that complies with the criteria of the language. not like different introductory books at the ground-breaking R approach, this ebook emphasizes programming, together with the foundations that follow to so much computing languages, and strategies used to advance extra complicated tasks. studying the language is made more straightforward via the common routines and end-of-chapter stories that assist you development expectantly during the e-book. ideas, datasets and any errata might be to be had from the book's website. the numerous examples, all from actual functions, make it really worthwhile for an individual operating in sensible info research.

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Extra resources for A first course in statistical programming with R

Example text

Missing values are not allowed for the condition, and will trigger an error. 3 A simple example: > x <- 3 > if (x > 2) y <- 2 * x else y <- 3 * x Since x > 2 is TRUE, y is assigned 2 * 3 = 6. If it hadn’t been true, y would have been assigned the value of 3 * x. The if()statement is often used inside user-defined functions. The following is a typical example. 4 The correlation between two vectors of numbers is often calculated using the cor()function. It is supposed to give a measure of linear association.

Are used to control the details of the display. 4 shows the result of the following code. > x <- rnorm(100) > hist(x) If you have n values of x, R, by default, divides the range into approximately log2 (n)+1 intervals, giving rise to that number of bars. For example, our data set consisted of 100 measurements. Since 100 > 26 = 64 100 < 27 = 128 6 < log2 (100) < 7, it can be seen that R should choose about 7 or 8 bars. 5 in this case). The above rule (known as the “Sturges” rule) is not always satisfactory for very large values of n, giving too few bars.

The above rule (known as the “Sturges” rule) is not always satisfactory for very large values of n, giving too few bars. Current research suggests that the number of bars should increase proportionally to n1/3 rather than proportional to log2 (n). The breaks = "Scott" and breaks = "Freedman-Diaconis" options provide variations on this choice. 5 shows the results for a 10 000 point dataset using the “Sturges” and “Scott” rules. 4 Box plots A box plot (or “box-and-whisker plot”) is an alternative to a histogram to give a quick visual display of the main features of a set of data.

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