Download PDF 100 Statistical Tests: in R, by Dr ND Lewis
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100 Statistical Tests: in R, by Dr ND Lewis
Download PDF 100 Statistical Tests: in R, by Dr ND Lewis
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100 Statistical Tests in R is designed to give you rapid access to one hundred of the most popular statistical tests. It shows you, step by step, how to carry out these tests in the free and popular R statistical package. The book was created for the applied researcher whose primary focus is on their subject matter rather than mathematical lemmas or statistical theory. Step by step examples of each test are clearly described, and can be typed directly into R as printed on the page. To accelerate your research ideas, over three hundred applications of statistical tests across engineering, science, and the social sciences are discussed.
- Sales Rank: #377168 in Books
- Published on: 2013-04-15
- Original language: English
- Number of items: 1
- Dimensions: 9.00" h x 1.06" w x 6.00" l, 1.37 pounds
- Binding: Paperback
- 468 pages
Most helpful customer reviews
18 of 18 people found the following review helpful.
If You Use R Code for Statistics, This is a Solid Reference
By Dr. Mitchell R. White
I'll say up front: This was a tough book to rate. However, upon reflection and a careful re-reading of the introductory matter, I decided on full marks. Mr. Lewis makes no pretense this is a textbook, and I'm sure it wouldn't suffice in that role. Rather, "100 Statistical Tests in R" provides a solid reference, with many worked examples, on inference procedures that many scientists and researchers need. Usually they need them without all the theoretical trappings, and that's where this book excels: "Just the tests, ma'am."
The presentation is spare and clean, with solid literature research. The R code appears to be up to date (at time of release, anyway), and package references are valid. An amazingly wide range of examples is shown, from communicating with whales to stock trading, game theory to medical applications.
My concerns are not with the quality of the test procedures or the code. I tried quite a few of the procedures, and found them to be functional and clear. The organization of the tests into groups covering correlation/causation, hypothesis testing, independence, and more is useful, and clearly shown early in the volume. I especially enjoy having more than one option even within a single test.
I am always a bit worried about efforts to enable sophisticated analyses and inference without sufficient context or support for the less-sophisticated researcher, who is tempted to use the procedure as a "black box" and then believe they know enough to decide and act. Many of these tests are like carving an object with a supremely sharp knife; if you're not a master carver you can lose some skin, or perhaps a finger. For those who need these tests but haven't serious grounding in their foibles, I strongly recommend developing a relationship with a practicing statistician and seeking guidance.
These concerns do not reduce the usefulness of this presentation of statistical tests. The author makes no claims about one's ability to correctly infer in a particular situation. His guidance is otherwise.
If you're looking for a listing of the mathematical equations for all these tests, you'll need to look elsewhere. However, if you're in a technical, research or development setting and use R (or have access to R coders to help), I heartily recommend this book to you.
12 of 13 people found the following review helpful.
Just do it.
By Dergie
Exactly what it says. If you know what test you want the book tells you how to do it in R. Very clear expanation with examples. Output explained, including stored output.
8 of 8 people found the following review helpful.
A Handy Desk Reference Guide
By Aaron J. Wallach
This is a very good list of statistical tests. It provides some basic application and usage examples and then an example of how to run the test in R.
I would suggest you have a solid understanding of statistics before purchasing as you will both have to know what you're looking for and the underlying concepts behind them; this is not "Statistics in R for Dummies". A knowledge of R is not required, but should of course be reccomended...
You get a lot more than the $3 price tag out of this, if you know how to use it....
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