Statistics Project

The purpose of the statistical project is to compare numerous attractive tabloid papers with high quality newspapers by trying to find statistical differences. To appeal to the mass on behalf of paper, I chose a mirror every day, and for text quality newspapers, I chose the era. I hope that there is some important statistical difference in the style of the news, I can comment. Data collection before testing: We decided to select approximately the same paragraph number and number of ads from "Time" and "Mirror" 4 to 5 pages or similar pages on pages 4 to 6. .

One of the projects was the collapse of the 2011 large linear equation. I would like to prove that our mathematical block is perfectly project based as an eight-year self-sufficiency teacher. After the statistics project succeeded, I decided to work on the "realistic linear equation" project. I ask students to find an example of linear equations that use this skill in everyday life and interview experts. Not to mention experts who can interview, students can not find enough examples. The project was forced to feel, the ultimate goal was not to find anything relevant. To make matters worse, it is difficult for students to determine linear functions when looking at charts or using algorithms to solve linear equations. At first, I accused my students. I think that they are lazy and not chaotic. However, four days after the project failed, I found that this is a design problem. Basically, these standards are not suitable for project-based approaches.

Brown University's Daniel Kuning is watching the theory. Visual and interactive presentation of probabilities and statistics covering topics from basic regression to linear regression. The purpose of this project is to make it easier for more students to access statistics through interactive visualization. Let's try deep learning in Python using Adam Geitgey's fully preset VM. How can I install and run all these open source libraries on my computer to answer this question? This is a wonderful resource for people who want to start using machine learning tutorials and want to simplify the setup process.