The lecture presents information about how the Internet works so students studying cyber security can better understand how cybercriminals commit their crimes. The lecture provides elemental concepts so students of all disciplines, from computer engineering to criminal justice and law can obtain a basic foundation.

With 38.5 billion smart devices in existence in 2020 and increasing every year, the potential for security breaches in the Internet of things is also escalating at a dramatic pace. The goal of this team activity is to facilitate team work, critical thinking, and presentation skills in the area of cybersecurity and the Internet of Things. Students will be grouped into two teams. As a team, they will analyze cases about security cameras and smart dolls through the questions presented in the activity. They will present their analysis to the class.

This presentation is about the Silk Road Market, one of the largest cases of illegal drug activity on the dark web, that the federal government has prosecuted. Beyond discussing the case, the presentation adds general facts about the US Department of Justice, the FBI and the DEA, and federal sentencing. The case discussion includes information about: Ross Ulbricht the creator and head of the market; how the Silk Road operated; the involvement of the FBI and DEA; the trial; the fourth amendment violations alleged by the defense; and the sentencing.

The Folger Shakespeare Library provides the full searchable text of "Cymbeline" to read online or download as a PDF. All of the lines are numbered sequentially to make it easier and more convenient to find any line.

This patient education program explains cystic fibrosis or CF, including the causes, symptoms, diagnosis, treatments, prevention, and key facts about the disease. This resource is a MedlinePlus Interactive Health Tutorial from the National Library of Medicine, designed and developed by the Patient Education Institute.

Welcome to DC Electrical Circuit Analysis, an open educational resource (OER). The goal of this text is to introduce the theory and practical application of analysis of DC electrical circuits. It is offered free of charge under a Creative Commons non-commercial, share-alike with attribution license. For your convenience, along with the free pdf and odt files, print copies are available at a very modest charge. Check my web sites for links.

This activity will help students understand how the enzyme telomerase works to solve the "end replication problem."

Persuasive Writing at Oregon State University

Short Description:
Arguments are all around us. Everywhere we look, someone is trying to get our attention, change our minds, or sell us something. Learning about how persuasion works will make you a more thoughtful and skeptical consumer of all that content, so that you can come to your own conclusions and recognize the underlying assumptions that inform those attempts to persuade you. This book is about analyzing others' arguments and crafting your own. The rhetorical choices that you make as a writer–from evidence to structure to tone–impact how your audience will receive your ideas. Using those tools effectively will help your voice be heard. Data dashboard

Word Count: 96049

ISBN: 978-1-955101-34-9

(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)

Are you ready to leave the sandbox and go for the real deal? Have you followed Data Analysis: Take It to the MAX() and Data Analysis: Visualization and Dashboard Design and are ready to carry out more robust data analysis?

In this project-based course you will engage in a real data analysis project that simulates the complexity and challenges of data analysts at work. Testing, data wrangling, Pivot Tables, sparklines? Now that you have mastered them you are ready to apply them all and carry out an independent data analysis.

For your project, you will pick one raw dataset out of several options, which you will turn into a dashboard. You will begin with a business question that is related to the dataset that you choose. The datasets will touch upon different business domains, such as revenue management, call-center management, investment, etc.

This course is for all of those struggling with data analysis. That crazy data collection from your boss? Megabytes of sensor data to analyze? Looking for a smart way visualize your data in order to make sense out of it? We’ve got you covered!

Using video lectures and hands-on exercises, we will teach you cutting-edge techniques and best practices that will boost your data analysis and visualization skills.

This course has been awarded with the Wharton-QS gold education award in the category Regional awards Europe.
We will take a deep dive into data analysis with spreadsheets: PivotTables, VLOOKUPS, Named ranges, what-if analyses, making great graphs – all those will be covered in the first weeks of the course. After that, we will investigate the quality of the spreadsheet model, and especially how to make sure your spreadsheet remains error-free and robust.

Finally, once we have mastered spreadsheets, we will demonstrate other ways to store and analyze data. We will also look into how Python, a programming language, can help us with analyzing and manipulating data in spreadsheets.

This course is created using Excel 2013 and Windows. Most assignments can be made using another spreadsheet program and operating system as well, but we cannot offer full support for all configurations.

Struggling with data at work? Wasting valuable time working in multiple spreadsheets to gain an overview of your business? Find it hard to gain sharp insights from piles of data on your desktop?

If you are looking to enhance your efficiency in the office and improve your performance by making sense of data faster and smarter, then this advanced data analysis course is for you.

If you have already sharpened your spreadsheet skills in Data Analysis: Take It to the MAX(), this course will help you dig deeper. You will learn advanced techniques for robust data analysis in a business environment. This course covers the main tasks required from data analysts today, including importing, summarizing, interpreting, analyzing and visualizing data. It aims to equip you with the tools that will enable you to be an independent data analyst. Most techniques will be taught in Excel with add-ons and free tools available online. We encourage you to use your own data in this course but if not available, the course team can provide.

These course materials are part of an online course of TU Delft. Do you want to experience an active exchange of information between academic staff and students? Then join the community of online learners and enroll in this MOOC. This course is part of the Data Analysis XSeries.

This open resources textbook contains 10 Units that describe and explain the main concepts in statistical analysis of psychological data (managing data, measures of central tendency, measures of spread, correlations, simple linear regression). In addition to conceptual descriptions and explanations of the basic analyses for descriptive statistics, this textbook also explains how to conduct those analyses with common statistical software (Excel) and open-source free software (R). This book is directed to undergraduates studying basic statistics, especially basic statistics in psychological research.

Course materials on using OpenRefine, a powerful tool for cleaning and transforming tabular data.

Course Description: This course covers the management of healthcare data, selected data management topics with current importance in the field, and how to use statistical methods in data analysis.

Learning Objectives: Upon completion of the course students should be able to:
1. Describe analytics and decision support.
2. Validate the reliability and accuracy of secondary data sources.
3. Identify data sources requiring data management and analytics skills.
4. Demonstrate the statistical methods used in data analysis.

This is a textbook for teaching data science using the Python programming language at a general first year undergraduate level.

This is a textbook for teaching data science using the R programming language at a general first year undergraduate level.

Cleaning, reshaping, and transforming data for analysis and visualization, with R and the Tidyverse

Word Count: 3515

(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)