Skaylar - Analyze datasets

Question

Skaylar

Find what doesn't add up

Skaylar is a simple, web-based tool for forensic data analysis using Benford's Law to analyze and visualize first-digit distributions in a dataset.
Paste the data, click Run Test, and instantly see if there are anomalies.

Benford's Law showing population of countries (1970, 1980, 1990, 2000, 2010, 2015, 2020, 2022)

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What is Benford's Law?

In real financial data, the digit "1" appears as the first digit ~30% of the time, "2" ~18%, etc.
If your data deviates too much, it can signal fraud, errors, or manipulation.
Skaylar checks this for you in seconds.

How to Use

1. Visit the website or download the repo (offline use):

git clone https://github.com/Temi-Tade/Skaylar.git
or click Code > Download ZIP and extract files on your computer.

2. Open

Double-click index.html
Works in Chrome, Edge, Firefox, and on mobile.

3. Analyze

1. Input/Paste your numbers in the textbox or Click Select Dataset to select/upload a .json dataset. Numbers in the textbox should be delimited by commas, spaces or new lines
2. Click Run Test
3. View the results table and graph

What You Get

• Results Table: Expected % vs Actual % for digits 1-9 and deviations
• Graph: Visual comparison to spot deviations fast
• Analytics: Max deviation and Chi square value.

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Height distribution (Does not follow Benford's Law)

Fibonacci series (Follows Benford's Law)

What you can do

• Customize Graph: Change colour of expected and actual curves on the graph. Also, you can scale the graph to different zoom levels.
• Save Datasets: Save a Dataset that you manually pasted/inputted in the text box as a .json file that you can share with other people.

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Save manually-inputted data as a .json Dataset file.

Customize curve colours on the graph and adjust zoom levels.

Contribute to Skaylar

Skaylar is open source and is open to contribution from developers, data scientists/analysts, forensic accountants, auditors and anyone interested in making it better.

Contribution Guidelines

• Fork the repo and make your improvements/additions/fixes.
• Check out the issues tab on the repo if you are confused in where to start from.
• Create a Pull Request from your forked repo.
• Your PR will be reviewed and merged accordingly.

You can also contribute by adding datasets for users to test Skaylar. The datasets are .json files and should strictly follow the format below:

{
    "name": "Name of the dataset", // recommended: separate words with underscores 
    "description": "Description of the dataset",
    "source": "Verified and official source", // You can put your name if you scrapped the data yourself 
    "data": [120, 300] // array of the numbers in the dataset
}