Announcing vvdoctor Alpha Release
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Announcing the Launch of vvdoctor: A Shiny App for Effortless Data Analysis
We are excited to announce the launch of vvdoctor, a new R Shiny app (and package) that provides a user-friendly interface for statistical testing from data! The goal is to aid to data-driven decision making from a statistical perspective. When is a difference large enough? Is there a notable increase from last year? Is there a difference between group A and B? These questions can be difficult to answer from solely a data-analytical perspective. vvdoctor alleviates this difficulty by easily allowing researchers, data analysts, and anyone interested in exploring data to easily conduct statistical tests from data! Upload your file, visualize your data, and perform a wide range of statistical tests in vvdoctor.
vvdoctor is now live and is accessible at: shinyapps.io. This app is the result of a collaborative effort by the team at Vusaverse, and it aims to simplify the process of conducting statistical tests from data.
Key Features
Seamless Data Uploading: With just a few clicks, you can upload your data files in various formats, including CSV, RDS, Parquet, and more. The app will automatically display the data in a dataframe.
Data Visualization: Generating histograms and other visualizations is a breeze. Simply select the variable you want to explore, and the app will generate the corresponding plot.
Comprehensive Statistical Testing:
vvdoctoroffers a wide range of statistical tests, including t-tests, ANOVA, correlations, and more. The app will guide you through the process of selecting the appropriate test based on the characteristics of your data.Interpretable Results: Once you’ve run a statistical test, the app will display the test statistic, p-value, and any other relevant information, making it easy to interpret the results.
Please refer to the vvdoctor GitHub repository of the project for further specification.
Getting Started
To start using vvdoctor, simply visit the app at shinyapps.io. Alternatively, you can install the package directly in R and run the app locally:
## Install the package
devtools::install_github("vusaverse/vvdoctor")
## Load the package and run the app
library(vvdoctor)
vvdoctor::diagnose()
Contributing and Feedback
This release of vvdoctor is an alpha-version. There are many improvements being made currently and many improvements to be made! We aim to polish up vvdoctor with the help of the R community! We’re committed to continuously improving vvdoctor and adding new features to make data analysis even more accessible. If you have any suggestions, ideas, or encounter any issues, please don’t hesitate to reach out to us. You can submit your feedback through GitHub issues or contribute to the project by submitting pull requests. We appreciate your support!
Happy analyzing!
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