A curated list of awesome Shiny Apps for statistics (ASAS) can help teachers teach basic statistics to their students and assist self-learners in visualizing statistics concepts.

Contents

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

Resources

• Awesome R Shiny – A curated list of resources for R Shiny.

Common Plots

• Boxplots & Histograms
• List of R graphs

Common Statistic

• Continuous Variables
  • Stability of Mean & Median
  • Correlation
• P-value
  • When does a significant p-value indicate a true effect?
  • Hack p-value
  • The Vovk-Sellke maximum p-ratio

Common Distribution

• Uniform
• Normal
• Binomial
• Students T
• F
• Chi-square
• Shiny Apps Including More Than One Distribution
  • Normal, Binomial, Students T, F, Chi-square

Random Samples

• Sampling and Standard Error
• Central Limit Theorem
  • Means
  • Proportions

Two Groups or Multiple Groups Comparison

• Cohen’s d
• ANOVA
  • Sums of Squares in ANOVA
  • BIC Approximation for ANOVA Designs

Hypothesis Testing

• Bootstrap Resampling – Demonstrate hypothesis testing using bootstrap resampling.
• Power – Demonstrate the relationship of statistical power, effect size, and false positives.
• Calculate Power – Calculate 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).

Linear Regression

• Simple Linear Regression
• Sum of Square in Simple Linear Regression – 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.

Nonlinear Models for Continuous Variables

K-means Clustering

• Estimate K
• Iris Dataset

Categorical Models

• Relationship between Test Accuracy, Precision, Sensitivity, and Specificity

Survival Model

• Hazard Model

Bayesian Analysis

• Bayes Factors
• Robustness Analysis for Bayes Factors: Two Sample T Test
• Bayesian Inference
• Posterior Distribution – Calculate posterior distribution based on different priors.
• Hypothesis Testing – Binomial & Normal Distribution

Longitudinal Analysis

• Longitudinal Data Exploration

Test Analysis

• Text Analysis of an Uploaded .txt File

Complete Data Analysis

• Linear Regression
• Shiny Data Demo

Help Wanted

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.

Troubleshooting

If you encounter issues while using the Awesome Shiny Apps for Statistics, here are a few troubleshooting ideas:

• Ensure that your internet connection is stable as Shiny Apps require an internet connection to function properly.
• If an app fails to load, try refreshing the page or clearing your browser cache.
• For any errors related to specific statistical concepts, refer to the provided resources or documentation linked within the apps.
• For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

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