{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

Introduction to R Spring - 2 of 13 1.1 Introducing R Figure...

Info iconThis preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon
2 of 13 1.1 Introducing R Figure 1: The Univac II, circa 1958. Figure 2: The program Z (1) = Y + W (1) on a punch card. Statistics and Computers The U.S. Bureau of the Census used the UNIVAC computer to process the 1950 Census data. In 1951, a report stated“it would take at least 650 keypunch operators, working on 17 document punch machines during the week of peak Census processing, to produce a million punched cards completely edited and ready for tabulation.” To realize productivity gains, and to pursue their interest in technical innovation, the Bureau acquired an electronic computing machine. 1.1 Introducing R It’s statistics program / language capable of most basic and advanced statistical procedures. Some benefits: It’s free (GNU General public license). Works on all major platforms. Compatible with S. Anthony Tanbakuchi MAT167
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Introduction to R 3 of 13 It’s a powerful calculator. It’s simple (therefore easy). It encourages reproducible research. S Version 3 (1983- (the `blue book’) Merged some new ideas with “Everything is an object” (inc functions). Functional evaluation model. .C(), .Fortran(), no Interface No direct back compatibility Statistical Models in S (S3) (the `white book’) An object-based approach. Model formulas (& terms objects). Data Frames (& model frames, …). S3 methods Give the user a simple call for plot, summary, predict, etc. Minimal additions to S engine & API Figure 3: Timeline of R. (Credit: From John M. Chambers 2006 talk.) Why not use another statistics package? We could, but most complete packages cost from hundreds to thousands of dollars! Since R can do basic through highly advanced statistics — and it’s free — it is a good choice! Why not use Excel? Excel, while an spreadsheet excellent package, is not a statistical software package. Even with its statistical (Analysis Tool Pack) add-in it will not be able to adequately perform all the necessary functions. Why not use a TI statistics calculator? We could use it for trivial prob- lems. But you’d not likely use it after the class for real data. It’s just not reasonable to enter large data sets (with potentially thousands of num- bers) into a calculator and you can’t readily put your work or graphs into a report. By teaching you R you will learn a real world statistics program that you can actually use in your work if needed. Since it’s free and accepted by the scientific community, you won’t have to ask your company to buy an expensive piece of software. Perhaps you can convince your boss to give you a raise since you’ve saved them thousands of dollars by using R! Four key things you must learn from this lecture By the end of this lecture, you must be able to: 1. Store a set of data (vector) in a variable.
Background image of page 2
Image of page 3
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}