A quick "hands on" activity for an in-class experience of data collection as a simple linear regression example where students predict the time needed for a human chain of hand squeezes to make a full circuit as a function of number of people in the chain. The lesson plan secondary school lesson plan adapted from Cynthia Lanius’ hand squeeze activity by Bo Brawner at Tarleton State University.
This handout lists the most commonly used effect sizes, adjustments, and rules of thumb concerning sample size calculation.
These cheat sheets make it easy to learn about and use some of the favorite packages of RStudio.
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.
This is a lesson plan for 16 to 17 year old students that focuses on developing students' understanding of the relative strengths and weaknesses of various representations of real world univariate statistics. Students work in groups to research different visual representations and create a wiki page of their findings.
This simulation illustrates least squares regression and how the least squares solution minimizes the sum of the squared residuals. The applet demonstrates, in a visual manner, various concepts related to least squares regression. These include residuals, sum of squares, the mean line, how the line of best fit is determined, and how the line of least squares solution minimizes the sum of the squared residuals.
StatKey is the analysis package to accompany the textbook "Statistics: Unlocking the Power of Data." StatKey includes interactive applets to describe and graph data, engage in bootstrapping and randomization tests, and explore sampling distributions and theoretical distributions.
This YouTube channel includes a series of video interviews between John McGready and some of his colleagues from Johns Hopkins University. The videos are meant to highlight the importance of biostatistics as a core driver of public health discovery, the importance of statistical reasoning in the research process, and how the fundamentals that are covered in an introductory biostatistics course are the framework for more advanced methodology.