README.Rmd

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output: github_document
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knitr::opts_chunk$set(
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# compstatslib

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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.

## Major Functions

Three types of functions are made available:

- **Interactive functions** let you use your mouse and/or keyboard to interact with a visualization of a technique (e.g., regression, PCA)
- **Plot functions** functions produce plots of data, distributions, or particular statistical concepts (often a non-interactive counterpart to an interactive function)
- **Code functions** are provided as examples of code that one might want to see (they are executable, but the major value is in seeing their code)

### Statistical Tests

- `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.

### Statistical Sampling

- `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.

### Linear Regression

- `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.

### Logistic Regression

- `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.

### Principal Components Analysis

- `interactive_pca()` Interactive visualization function that lets you point-and-click to add data points, while it automatically plots and updates principal component vectors.

### Precision

- `machine_precision()` Code function that shows how to find the smallest number your computer can effectively represent

### Linear Algebra

- `interactive_matrix_inverse()` Interactive function that allows one to *manipulate* a matrix inversion.
- `visualize_inverse()` Plotting function that helps visual an inverse.

## Installation

You can install the current development version from [GitHub](https://github.com/) using the `devtools` package:

``` r
# install.packages("devtools")
devtools::install_github("soumyaray/compstatslib")
```

Feel free to send open issues or send pull requests. Happy hacking!