Rsquared Academy uses R packages for teaching business analytics/ data science courses. In the process, we created a few packages and would like to share them with the community in the hope that others will find it useful in teaching and learning data science with R.
Our goal is to design and develop R packages which are:
- User friendly
- Light weight
- Well tested
- Well documented
Our developers are proactive and respond to your concerns in a timely manner. We may not be able to fix bugs or add new features outright but try to do so to the best of our ability. We are quick to fix any major bugs or issues that may affect our users.
olsrr
Tools for building linear regression models
- Comprehensive Regression Output
- Variable Selection Procedures
- Heteroskedasticity Tests
- Collinearity Diagnostics
- Model Fit Assessment
- Measures of Influence
- Residual Diagnostics
CRAN
GitHub
Docs
xplorerr
Tools for interactive data analysis
- Descriptive Statistics
- Inferential Statistics
- Visualize Probability Distributions
- Data Visualization
- RFM Analysis
- Linear Regression
- Logistic Regression
CRAN
GitHub
Docs
descriptr
Tools for generating descriptive/summary statistics
- Data Screening
- Summary Statistics
- Frequency Tables
- Cross Tables
- Data Visualization
CRAN
GitHub
Docs
inferr
Tools for inferential statistics
- Binomial Test
- Levene's Test
- Test of Proportion
- Test of Variance
- t Test
- Chi Square Test
- McNemar Test
- Cochran Q Test
- Runs Test
CRAN
GitHub
Docs
blorr
Tools for builing binary logistic regression models
- Bivariate Analysis
- Model Fit Statistics
- Model Validation
- Variable Selection
- Residual Diagnostics
- Collinearity Diagnostics
- Visualization
CRAN
GitHub
Docs
vistributions
Tools for visualizing probability distributions
- Binomial Distribution
- Chi Square Distribution
- Normal Distribution
- f Distribution
- t Distribution
- Includes Shiny App
CRAN
GitHub
Docs
nse2r
Fetch data from the National Stock Exchange, India
- Most Actively Traded Stocks
- NSE Top Gainers & Losers
- 52 Week High & Low
- Index Quote
- Top F&O Gainers & Losers
- Pre Open Market Data
- Advances & Declines
- Includes Shiny App
CRAN
GitHub
Docs