Web Content Rx
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Web Content Rx
Web Content Rx is a hands-on primer that shows anyone—even technical novice—show to write high-quality, keyword-laden, search engine optimized Web content. Based on the latest research on how people read the Web, it also includes numerous tips, tricks, and techniques on writing a blog, training, and creating an audio or video podcast. This must-have reference is for anyone working on the Web. Webmasters can avoid losing projects for lack of content. Business people can now create effective, readily understood Web content about their services or products. eBay sellers can create powerful online advertisements and photograph your products to maximize their appeal. Technical writers, and those who write for industry, will appreciate the extensive safety-related material.
Digital learning content: a designer's guide
This guide is for anyone with an interest in helping others to learn. You may be a teacher, trainer, lecturer or coach. You may be a subject expert with knowledge you want to share or an experienced practitioner who wants to pass on their tips. You may already be a creator of learning content, looking to update their skills. Whatever your interest, this guide will help you to design learning materials that really make a difference. Digital learning content takes a wide variety of forms, including tutorials, scenarios, podcasts, screencasts, videos, slideshows, quizzes and reference materials. This guide provides you with fundamental principles that you can apply to any content creation activity as well as practical information relating to specific content types. We are fast approaching a point where all learning content will be digital and online. It's time to join the revolution, to contribute as much as you consume. Your learning journey starts here.
R by Example
Author: Jim Albert
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-01-28
R by Example is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functions are presented in the context of interesting applications with real data. The purpose of this book is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics. Specifically, this book is written for users who have covered at least the equivalent of (or are currently studying) undergraduate level calculus-based courses in statistics. These users are learning or applying exploratory and inferential methods for analyzing data and this book is intended to be a useful resource for learning how to implement these procedures in R.