Overview of the RGB color model.
Collaborative robotic sensors
Introduction to why we would need RSA. Created by Brit Cruise.
Setting up a trapdoor one-way function. Created by Brit Cruise.
RSA Encryption (step 3). Created by Brit Cruise.
RSA worked example. Created by Brit Cruise.
This book is designed first and foremost for College of DuPage students in Sociology 1205 (Introduction to Data Science) and Sociology 2200 (Introduction to Research Methods), but it can be just as easily used by anyone looking to learn the basics of the R language in the R Studio environment. In addition, this book is written specifically for people with absolutely no experience in coding or data science.
This resource will be updated as needed. For the most recent version, visit: https://cod.pressbooks.pub/introduction2r/front-matter/introduction/
How could random numbers speed up a decision algorithm? Created by Brit Cruise.
Introduction to random primality tests & how they will work (warm up). Created by Brit Cruise.
Pamela shows the difference between unreadable code and readable code. Go for the latter!
Children are surrounded – and targeted – by advertisements: on television, the computer, even on their journeys to and from school. Children need specific strategies for reading and talking about advertisements and their impact. Reading Ads with a Social Justice Lens is a series of 13 multidisciplinary mini-lessons that provide such strategies and build critical literacy. The lessons are designed for students in grades K-5 and include suggestions for simple adaptations. These lessons open up important conversations about the relationship between advertisements and social justice. Children will see that they have the power to decide how media will influence them. They will also engage in social justice projects that address some of the unfair messages they find in advertising.
Half a century after they were first described, relational database systems remain by far the most popular choice for the storage of large datasets. The book starts by describing the practical and theoretical reasons why this is so.
It then shows how to analyse a data requirement and use it to design and develop a database. Through a series of practical exercises and prepared scripts, it teaches SQL, using a freely downloadable, fully working database system (SAP SQL Anywhere™ for Windows 7 and above, MacOS 10.9 and above, and Linux)
The author works as an independent consultant. He had a career in database systems, and taught the subject for more than two decades, as a course tutor for the UK Open University. He is a Fellow of the Higher Education Academy.
This text is a free introductory text that introduces MS Access and relational database design. The motivation is to support a second-year course on database systems which, to the student, is either a service course providing an introduction to database concepts, or, as a prerequisite for more advanced study in the field.
Scientific code is different from production software. Scientific code, by producing results that are then analyzed and interpreted, participates in the elaboration of scientific conclusions. This imposes specific constraints on the code that are often overlooked in practice. We articulate, with a small example, five characteristics that a scientific code in computational science should possess: re-runnable, repeatable, reproducible, reusable and replicable. The code should be executable (re-runnable) and produce the same result more than once (repeatable); it should allow an investigator to reobtain the published results (reproducible) while being easy to use, understand and modify (reusable), and it should act as an available reference for any ambiguity in the algorithmic descriptions of the article (replicable).
A short online tutorial to introduce readers to research best-practices in the humanities and social sciences.
Learn how to resize shapes proportionally to each other with fractions and variable expressions.
An overview of restricting grouped results with HAVING
This is the website for “R for Data Science”. This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data science. Just as a chemist learns how to clean test tubes and stock a lab, you’ll learn how to clean data and draw plots—and many other things besides. These are the skills that allow data science to happen, and here you will find the best practices for doing each of these things with R. You’ll learn how to use the grammar of graphics, literate programming, and reproducible research to save time. You’ll also learn how to manage cognitive resources to facilitate discoveries when wrangling, visualising, and exploring data.
This lesson in part of Software Carpentry workshop and teach novice programmers to write modular code and best practices for using R for data analysis. an introduction to R for non-programmers using gapminder data The goal of this lesson is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation. Note that this workshop will focus on teaching the fundamentals of the programming language R, and will not teach statistical analysis. The lesson contains more material than can be taught in a day. The instructor notes page has some suggested lesson plans suitable for a one or half day workshop. A variety of third party packages are used throughout this workshop. These are not necessarily the best, nor are they comprehensive, but they are packages we find useful, and have been chosen primarily for their usability.
Through the two lessons and five activities in this unit, students' knowledge of sensors and motors is integrated with programming logic as they perform complex tasks using LEGO MINDSTORMS(TM) NXT robots and software. First, students are introduced to the discipline of engineering and "design" in general terms. Then in five challenge activities, student teams program LEGO robots to travel a maze, go as fast/slow as possible, push another robot, follow a line, and play soccer with other robots. This fifth unit in the series builds on the previous units and reinforces the theme of the human body as a system with sensors performing useful functions, not unlike robots. Through these design challenges, students become familiar with the steps of the engineering design process and come to understand how science, math and engineering including computer programming are used to tackle design challenges and help people solve real problems. PowerPoint® presentations, quizzes and worksheets are provided throughout the unit.