Statistics Education

  • 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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  • Online Statistics: An Interactive Multimedia Course of Study is a resource for learning and teaching introductory statistics. It contains material presented in textbook format and as video presentations. This resource features interactive demonstrations and simulations, case studies, and an analysis lab. 

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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.  These data sets provide facts from across the globe such as average income, life expectancy, energy use, education levels, and much more.

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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.

    Download Gapminder’s slides, tools, posters, handouts, lesson plans, and presentations at this webpage.

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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.

    This particular page gives teachers resources to use in their classrooms involving the tools and data found on Gapminder.

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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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