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Statistical Computing with R: A tutorial. 0.1. What is R? R is a software package especially suitable for data analysis and graphical representation. Functions and results of analysis are all stored as objects, allowing easy function modification and model building. R provides the language, tool, and environment in one convenient package. It is very flexible and highly customizable. Excellent graphical tools make R an ideal environment for EDA (Exploratory Data Analysis).

Since most high level functions are written in R language itself, you can learn the language by studying the function code. On the other hand, R has a few weaknesses. 0.2 Where do I get R? And follow the download instructions. 0.3 Invoking RIf properly installed, usually R has a shortcut icon on the desktop screen and/or you can find it under Start|Programs|R menu.

To quit R, type q() at the R prompt (>) and press Enter key. Commands you entered can be easily recalled and modified. When finished, click. (4) 10 awesome tools a happy startup shouldn’t live... - happystartups - Quora. 1. Lean Canvas If you’re an early stage startup the last thing you want to have to do is write a 30 page business plan. Wouldn’t it be great if you document your business model on one page, allowing you to focus on actually building your business? This great tool lets you adopt the principles of the business model canvas using a simple web interface. 2. Trello is a handy (and addictive) app that allows teams to collaboratively organise anything you can imagine. 3. Ok so this is a bit of a shameless plug. 4. This is a must app for those less technically inclined ;) If you’re looking for a cost effective way to produce a simple, mobile-optimised one page website, Strikingly is your new best friend. 5.

A great little piece of software by UX experts and neighbours of ours in Brighton, Clearleft, Silverback lets you record live usability tests through your built-in webcam (and mic) for watching or sharing later. 6. Mailchimp is a joy to use for email marketing. 7. 8. 9. 10. 11. Mathematica: Technical Computing Software—Taking You from Idea to Solution. With energetic development and consistent vision for three decades, Mathematica stands alone in a huge range of dimensions, unique in its support for today's technical computing environments and workflows.

A Vast System, All Integrated Mathematica has over 6,000 built-in functions covering all areas of technical computing—all carefully integrated so they work perfectly together, and all included in the fully integrated Mathematica system. Not Just Numbers, Not Just Math—But Everything Building on three decades of development, Mathematica excels across all areas of technical computing—including neural networks, machine learning, image processing, geometry, data science, visualizations and much more. Unimaginable Algorithm Power Mathematica builds in unprecedentedly powerful algorithms across all areas—many of them created at Wolfram using unique development methodologies and the unique capabilities of the Wolfram Language. Higher Level Than Ever Before Superfunctions, meta-algorithms...

R, the Software, Finds Fans in Data Analysts. One Page R: A Survival Guide to Data Science with R. Point / Counterpoint - The Case for Commodity & Open-Source Analytics. To save this item to your list of favorite AllAnalytics content so you can find it later in your Profile page, click the "Save It" button next to the item. Beth SchultzGood Data, Smarter Travel 4|24|14 | 2:50 | (0) comments Charged with keeping track of travel assets, including employees, iJET International relies on data management best-practices and advanced analytics to keep its clients in the know on current and potential world events affecting travel, Rich Murnane, Director of Enterprise Data Operations & Data Architect, told All Analytics in an interview from the 2014 SAS Global Forum Executive Conference.

Beth SchultzHealthcare Data Needs a Booster 4|23|14 | 2:39 | (0) comments W. Ed Hammond, Director of the Duke Center for Health Informatics, spoke from the recent 2014 SAS Global Forum Executive Conference about the data management challenges involved in healthcare today. Beth SchultzAnalytic Myths: True or False? Related posts: — Michael Steinhart, Related post: RStudio - Home. One Page R: A Survival Guide to Data Science with R.