Approximating a normal distribution with a binomial distribution
Approximating a normal distribution with a binomial distribution
Find the best linear fit for a given set of data points and residuals (or let this app show you how it is done).
Adjust regression parameters to bend and shift a two-dimensional polynomial surface.
When does a significant p-value indicate a true effect? This app will help with understanding the Positive Predictive Value (PPV) of a p-value.
This app is based on Ioannidis, J. P. A. (2005). Why most published research findings are false. PLoS Medicine, 2(8), e124. http://doi.org/10.1371/journal.pmed.0020124
Can you "see" a group mean difference, just by eyeballing the data? Is your gut feeling aligned to the formal index of evidence, the Bayes factor?
Visualizing the Bayes factor (quantification of evidence supporting a null or altermative hypothesis) using the urn model.
This page presents a series of tutorials and interdisciplinary case studies that can be used in a variety of blended as well as brick-and-mortar courses. The materials can be used in introductory level data science courses as well as more advanced data science or statistics courses. These materials assume that students have a basic prior knowledge of R or Rstudio.
Correspondence analysis is a method allowing you to describe synthetically a contingency table in which homogeneous individuals are classified on two criterias (or categorical variables, continuous ones being usable if discretized). This resource tells how it can be used, graphical representations of this process, and gives examples of it in action.
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.
This applet builds confidence intervals for the percentage of orange candies in box with two colors of candies. A smaller box visualizes the sample, and a graph keeps track of the location of the confidence interval. Students can take one sample (producing one CI) repeatedly, or take 100 random samples at once. The population percentage is hidden from view unless the student asks to see it, in which case it is displayed on the graph of confidence intervals. This allows the students to see whether each interval "hits" or "misses". Several parameters can be varied: sample size, confidence level and number of samples. A set of questions alongside the applet guides students.