Resource Library

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.

Whatever you can see on your screen, SnagIt will easily capture for your immediate use. Once you've taken your capture, SnagIt lets you edit, enhance, save, and use the capture for numerous tasks.

The program DistCalc calculates probabilities and critical values for the most important distributions. The purpose of this program is to show the concept of critical values and the replacement of printed distribution tables. The Distribution Calculator offers calculations for the normal distribution, the t distribution, the chi-square distribution, and the F distribution.

This site has a wide collection of statistical resources inluding an online textbook covering first-year non-calculus based statistics (e.g. Normal distribution, ANOVA, Chi-Square), a simulation/demonstration section containing Java Applets on these first-year topics (ANOVA, Binomial Distribution,Central Limit Theorem, Chi Square, Confidence Interval, Correlation, Central Tendency, Effect Size, Goodness of Fit, Histogram, Normal Distribution, Power, Regression, Repeated Measures, Restriction of Range, Sampling Distribution, Skew, t-test, Transformations), and case studies covering the topics in the first-year statistics course. There is also a page with some basic statistical analysis tools that will aid in doing the computations if you have a Java enabled browser.  The source code for these resources can also be downloaded from this site.

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. 

A collection of Java applets and simulations covering a range of topics (descriptive statistics, confidence intervals, regression, effect size, ANOVA, etc.).

This is a web application framework for R, in which you can write and publish web apps without knowing HTML, Java, etc. You create two .R files: one that controls the user interface, and one that controls what the app does. The site contains examples of Shiny apps, a tutorial on how to get started, and information on how to have your apps hosted, if you don't have a server.

This applet simulates rolling dice and displays the outcomes in a histogram. Students can choose to roll 1, 2, 6, or 9 dice either 1, 10, 20, or 100 times. The outcome studied is the sum of the dice and a red line is drawn on the histogram to show expected number of occurences of each outcome.

The Food and Drug Administration requires pharmaceutical companies to establish a shelf life for all new drug products through a stability analysis. This is done to ensure the quality of the drug taken by an individual is within established levels. The purpose of this out-of-class project or in-class example is to determine the shelf life of a new drug. This is done through using simple linear regression models and correctly interpreting confidence and prediction intervals. An Excel spreadsheet and SAS program are given to help perform the analysis. Key words: prediction interval, confidence interval, stability

This group activity focuses on conducting an experiment to determine which of two brands of paper towels are more absorbent by measuring the amount of water absorbed. A two-sample t-test can be used to analyze the data, or simple graphics and descriptive statistics can be used as an exploratory analysis. Students are asked to think about design issues, and to write a short report stating their results and conclusions, along with an evaluation of the experimental design. Key words: Two-sample t-test