awesome-shiny-apps-for-statistics
github.com/huyingjie/awesome-shiny-apps-for-statistics ↗🌟 A curated list of Awesome Shiny Apps for Statistics (ASAS)🌟
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me k-means clustering resources from awesome-shiny-apps-for-statistics"
Installation instructions →What's inside
Resources
- Awesome R Shiny
A curated list of resources for R Shiny.
Bayesian Analysis
- Bayes factors
- Bayesian Inference
- Binomial & Normal Distribution
- Posterior distribution
Documentation - Calculate posterior distribution based on different priors
- Robustness analysis for Bayes factors: Two sample t test
Two groups or multiple groups comparison
Hypothesis Testing
- Bootstrap resampling
Demonstrate hypothesis testing using bootstrap resampling.
- Calculate power
Calculat the power of a statistical hypothesis test for a two-sided symmetrical test and show how statistical power is related to the p-value and the significance level.
- Power
Demonstrate the relationship of statistical power, effect size, and false positives
- Trade Off
Visualize the trade off between type I and type II errors in a Null Hypothesis Significance Test (NHST).
Common Plots
Common Statistic
- Correlation
- Hack p-value
- Stability of Mean & Median
- the Vovk-Sellke maximum p-ratio
the maximum diagnosticity of a two-sided p-value.
- When does a significant p-value indicate a true effect?
Linear Regression
- Diagnostics for simple linear regression
- Fit a simple linear regression model
- Graphs for linear regression with high orders
- Influence analysis
Demonstrates the leverage and influence of an adjustable point/outliers
- Meta analysis
Code
- Model selection
Choose models between simple regression, additive regression, and interactive models.
Nonlinear Models for Continous Variables
- Estimate KK-means Clustering
- Iris datasetK-means Clustering
Showing a sample of 46 resources. View the full list on GitHub →