A curated list of awesome Shiny Apps for statistics (ASAS) can

- help teachers teach basic statistics to their students.
- help self-learners to visualize statistics concepts.

- Resources
- Common Plots
- Common Statistic
- Common Distribution
- Random Samples
- Two Groups or Multiple Groups Comparison
- Hypothesis Testing
- Linear Regression
- Nonlinear Models for Continous Variables
- Categorical Models
- Survival Model
- Bayesian Analysis
- Longitudinal Analysis
- Test Analysis
- Complete Data Analysis
- Help Wanted

- Awesome R Shiny - A curated list of resources for R Shiny.

- continuous variables
- p-value
- When does a significant p-value indicate a true effect?
- Hack p-value
- the Vovk-Sellke maximum p-ratio - the maximum diagnosticity of a two-sided p-value.

- Uniform
- Normal
- Binomial
- Student's T
- F
- Chi-square
- Shiny Apps including more than one distribution

- Sampling and standard error
- Central Limit Theorem

- Bootstrap resampling - Demonstrate hypothesis testing using bootstrap resampling.
- Power - Demonstrate the relationship of statistical power, effect size, and false positives
- 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.
- Trade Off - Visualize the trade off between type I and type II errors in a Null Hypothesis Significance Test (NHST).

- Simple linear regression
- Sum of Square in simple linear regression | Code - Explore how sums of squares are calculated in simple linear regressions.
- Fit a simple linear regression model
- Diagnostics for simple linear regression
- Uncertainty
- Influence analysis - Demonstrates the leverage and influence of an adjustable point/outliers
- Graphs for linear regression with high orders
- Multicollinearity
- Model selection - Choose models between simple regression, additive regression, and interactive models.
- others

- Estimate K
- K-means Clustering

- Bayes factors
- Robustness analysis for Bayes factors: Two sample t test
- Bayesian Inference
- Posterior distribution | Documentation - Calculate posterior distribution based on different priors
- Hypothesis Testing

Several ways you can help

- Create a Shiny App that explains the statistics concept missing on the list
- Add latest and greatest Shiny Apps that explain statistics concepts
- Delete broken links to Shiny Apps
- Delete links to low-quality Shiny Apps
- Design the appearance of the website
- Fix any typo
- Rewrite the title or description of any Shiny App to make them more easily understood
- Suggest different ways to categorize

Please adhere to the contribution guidelines.

This work is licensed under a Creative Commons Attribution 4.0 International License.