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Probability

• Normal v. Binomial Distribution (Shiny App)

Approximating a normal distribution with a binomial distribution

• A First Lesson in Bayesian Inference (uses Shiny Apps)

This page supports an in-class exercise that highlights several key Bayesian concepts. The scenario is as follows: a large paper bag contains pieces of candy with wrappings of different color, and we are interested in learning about the unknown proportion of yellow-wrapped pieces of candy. After completing the exercises, we will be familiar with the following concepts and ideas: probability distributions can quantify degree of beliefprior distributionposterior distributionsequential updatingconjugacy, Cromwell’s Rule (http://en.wikipedia.org/wiki/Cromwell's_rule), the data overwhelm the prior, Bayes factors, Savage-Dickey density ratio, sensitivity analysiscoherence.

• Getting used to R, RStudio, and R Markdown

This resource is designed to provide new users to R, RStudio, and R Markdown with the introductory steps needed to begin their own reproducible research. Many screenshots and screencasts (with no audio) will be included, but if further clarification is needed on these or any other aspect of the book, please create a GitHub issue here or email me with a reference to the error/area where more guidance is necessary.  It is recommended that you have R version 3.3.0 or later, RStudio Desktop version 1.0 or higher, and rmarkdown R package version 1.0 or higher.

• Getting Started with R

These handouts/links give a foundational understanding of how to set up and use R

• Practicing Statistics: Guided Investigations for the Second Course

The goal of this text is to provide a broad set of topics and methods that will give students a solid foundation in understanding how to make decisions with data. This text presents workbook-style, project-based material that emphasizes real world applications and conceptual understanding. Each chapter contains:

• An introductory case study focusing on a particular statistical method in order to encourage students to experience data analysis as it is actually practiced.
• guided research project that walks students through the entire process of data analysis, reinforcing statistical thinking and conceptual understanding.
• Optional extended activities that provide more in-depth coverage in diverse contexts and theoretical backgrounds. These sections are particularly useful for more advanced courses that discuss the material in more detail. Some Advanced Lab sections that require a stronger background in mathematics are clearly marked throughout the text.
• Data sets from multiple disciplines and software instructions for Minitab and R.

The text is highly adaptable in that the various chapters/parts can be taken out of order or even skipped to customize the course to your audience. Depending on the level of in-class active learning, group work, and discussion that you prefer in your course, some of this work might occur during class time and some outside of class.

• Statistics Forum TalkStats.com

Statistics forum for questions/conversations ranging from homework problems in statistics and probability and help using statistical software to statistical research inquiries and career advising.

• Song: Central Limit Theorem

A song for use in helping students to recognize when the Central Limit Theorem applies.  Music & Lyrics ©2016 by Greg Crowther from Everett Community College. This song is part of an NSF-funded library of interactive songs that involved students creating responses to prompts that are then included in the lyrics (see www.causeweb.org/smilesfor the interactive version of the song, a short reading covering the topic, and an assessment item).

• The Probability Web

The Probability Web is a collection of probability resources designed to be especially helpful to researchers, teachers, and people in the probability community.  Web page links on this site include probabilty/statistics books and journals, information on mathematics and statistics-based careers, statistical software, teaching resources on probabilty topics, and more.

• STatistics Education Web (STEW)

Statistics and probability concepts are included in K–12 curriculum standards—particularly the Common Core State Standards—and on state and national exams. STEW provides free peer-reviewed teaching materials in a standard format for K–12 math and science teachers who teach statistics concepts in their classrooms.

STEW lesson plans identify both the statistical concepts being developed and the age range appropriate for their use. The statistical concepts follow the recommendations of the Guidelines for Assessment and Instruction in Statistics Education (GAISE) Report: A Pre-K-12 Curriculum Framework, Common Core State Standards for Mathematics, and NCTM Principles and Standards for School Mathematics. The lessons are organized around the statistical problemsolving process in the GAISE guidelines: formulate a statistical question, design and implement a plan to collect data, analyze the data by measures and graphs, and interpret the data in the context of the original question. Teachers can navigate the STEW lessons by grade level and statistical topic.

• Analysis Tool(s): JSE Archive of Interactive Computing (includes JAVA Applets)

The Journal of Statistics Education provides a collection of Java applets and excel spreadsheets (and the articles associated with them) from as early as 1998 on this webpage.