This R Package is a collection of interactive tools and helper functions that help teachers and learners learn concepts in computational statistics. Useful for homework, in-class demonstrations, or self-learning.
Three types of functions are made available:
interactive_t_test()
Interactive visualization function that will
show you a simulation of null and alternative distributions of the
t-statistic. You will be able to play with the different parameters
that affect hypothesis tests in order to see how their variation
influences the null t and alternative t distributions, as well as
statistical power.interactive_sampling()
Interactive sampling simulation that will
sample given population data to show how a sampling statistic is
distributed across repetitions of sampling exercise.plot_sample_ci()
Simulated visualization of samples drawn from a
given population function, with each sample’s confidence intervals
displayed.interactive_regression()
Interactive visualization function that
lets you point-and-click to add data points, while it automatically
plots and updates a regression line and associated statistics.plot_regr()
Plotting function that takes a dataframe of points
(x, y) and plots them with a regression line and associated
statistics.interactive_logit()
Interactive visualization function that lets you
point-and-click to add data points, while it automatically plots and
updates a logistic regression line and associated statistics.plot_logit()
Plotting function that takes a dataframe of points
(x, y) and plots them with a logistic regression curve and associated
statistics.interactive_pca()
Interactive visualization function that lets you
point-and-click to add data points, while it automatically plots and
updates principal component vectors.machine_precision()
Code function that shows how to find the
smallest number your computer can effectively representinteractive_matrix_inverse()
Interactive function that allows one to
manipulate a matrix inversion.visualize_inverse()
Plotting function that helps visual an inverse.You can install the current development version from
GitHub using the devtools
package:
# install.packages("devtools")
devtools::install_github("soumyaray/compstatslib")
Feel free to send open issues or send pull requests. Happy hacking!
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