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  • This is a graduate level course/collection of lessons in analysis of variance (ANOVA), including randomization and blocking, single and multiple factor designs, crossed and nested factors, quantitative and qualitative factors, random and fixed effects, split plot and repeated measures designs, crossover designs and analysis of covariance (ANCOVA). Perfect for students and teachers alike looking to learn/acquire materials on ANOVA.

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  • This graduate level course offers an introduction into regression analysis. A researcher is often interested in using sample data to investigate relationships, with an ultimate goal of creating a model to predict a future value for some dependent variable. The process of finding this mathematical model that best fits the data involves regression analysis.  STAT 501 is an applied linear regression course that emphasizes data analysis and interpretation and is perfect for both students and teachers of statistics courses.

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  • As our economy, society, and daily life become increasingly dependent on data, work across nearly all fields is becoming more data driven, affecting both the jobs that are available and the skills that are required. At the request of the National Science Foundation, the National Academies of Sciences, Engineering, and Medicine were asked to set forth a vision for the emerging discipline of data science at the undergraduate level. The study committee considered the core principles and skills undergraduates should learn and discussed the pedagogical issues that must be addressed to build effective data science education programs. Data Science for Undergraduates: Opportunities and Options underscores the importance of preparing undergraduates for a data-enabled world and recommends that academic institutions and other stakeholders take steps to meet the evolving data science needs of students. 

     

    Watch the report release webinar here:  https://vimeo.com/269033724  

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  • RStudio Cloud makes it easy for professionals, hobbyists, trainers, teachers and students to do, share, teach and learn data science using R.  Create analyses using RStudio directly from your browser - there is no software to install and nothing to configure on your computer.  Share your projects - and access those of others - without worrying about data transfer or package installation. Each project defines its own environment, and RStudio Cloud automatically reproduces that environment whenever anyone accesses the project.  It’s easy to share analyses with the world - but it’s also simple to collaborate with a select group in a private space. You control who can enter a space - and via roles, you have fine grained control over what each user can do.  There are also many learning materials available: interactive tutorials covering the basics of data science, cheatsheets for working with popular R packages, links to Datacamp courses, and a guide to using RStudio Cloud.

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  • swirl is a software package for the R programming language that turns the R console into an interactive learning environment. Users receive immediate feedback as they are guided through self-paced lessons in data science and R programming.

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  • Gapminder seeks to educate all on the importance of "factfulness" and of knowing and contextualizing the statistics that describe the state of our world.  Learn facts from across the globe such as average income, life expectancy, energy use, education levels, and much more.

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  • CATS, established in 1978, promotes the statistical sciences, statistical education, statistics applications, and related issues affecting the statistics community. The mission and scope of CATS evolved over time as interdisciplinary collaboration increasingly shaped the character of scientific research. After a brief hiatus, CATS was reconstituted in 2011 and has since focused on improving the visibility and practice of statistics within government agencies not well connected to statistics, increasing attention to statistical issues of big data and data science, and helping agencies identify bottlenecks impairing their analysis capabilities. Its multidisciplinary members are experts from statistics and related fields and leaders in diverse areas of interdisciplinary research, including the analysis of large-scale data, computational biology and bioinformatics, spatial data, environmental science, neuroscience, health care policy, and complex computer experiments.

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  • Everyday, massive amounts of data are generated in every part of our lives. That makes data fluency an indispensable skill to help you succeed - no matter what industry you’re in -- and DataCamp is here to help.  With bite-sized lessons in how to use R, Python, and SQL for data science, DataCamp allows you to learn in a way that fits your schedule, on any device.

    9 courses are available for those who create a free account, and 123 courses are available for individuals who sign up for a $29/month membership ($25/month is you pay yearly).  Businesses can also pay $300 per member per year for employees to learn these skills.

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  • How can we accurately model the unpredictable world around us? How can we reason precisely about randomness? This course will guide you through the most important and enjoyable ideas in probability to help you cultivate a more quantitative worldview.

    By the end of this course, you’ll master the fundamentals of probability and random variables, and you’ll apply them to a wide array of problems, from games and sports to economics and science.  This course includes 62 interactive quizzes and more than 400 probabilty-based problems with solutions.  Access to this course requires users to sign up for a free account.

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  • The International Society for Bayesian Analysis (ISBA) was founded in 1992 to promote the development and application of Bayesian analysis. By sponsoring and organizing meetings, publishing the electronic journal Bayesian Analysis, and other activities, ISBA provides an international community for those interested in Bayesian analysis and its applications.

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