04 Oct Benford`s Law 2020 Election Github

Several graphs have circulated online that question the authenticity of the election results. However, these graphs only show data in some states. Jupyter notebooks to analyze different districts/districts for the 2020 election. Each notebook contains a source URL for the dataset or a link to the table that was downloaded and crawled. This app takes open records from the LTSB`s open data page to retrieve election data for each Wisconsin district for the general election. If you don`t know Benford`s law, it`s an algorithm used to determine anonosomes in the number distribution. This program applies the algorithm to all total votes in the constituency, as well as to the vote of each party`s candidates, by extracting the main numeric from these vote counts and placing them in an entire table that mimics the 1-9 value distribution. Based on the total number of districts, the appropriate scale of the Benford curve is determined to refer to the distribution of each party in order to easily recognize anomalies. There was a problem preparing your code space, please try again. Benford Act Application to Wisconsin Open Election Data All data comes from www.politico.com/. Issues are used to track todos, bugs, feature requests, etc. When problems are created, they appear here in a searchable and filterable list.

To get started, you need to create a problem. Graphs of first census digits in different districts and districts for selected counties/cities. Benford`s law is an observation on the frequency distribution of principal digits in many real sets of numerical data. This site aims to present the results of the two candidates side by side against Benford`s Law in an easily digestible form. If nothing happens, download GitHub Desktop and try again. Benford`s law, also known as the Newcomb-Benford law, the law of abnormal numbers or the law of the first digit, is an observation of the frequency distribution of principal digits in many real sets of numerical data. The law states that in many natural collections of numbers, the main number is likely to be small. For example, in quantities that obey the law, the number 1 appears as a significant figure in about 30% of cases, while 9 appears as the main significant figure in less than 5% of cases. If the numbers were evenly distributed, they would each occur about 11.1% of the time.

Benford`s law also makes predictions about the distribution of second digits, third digits, combinations of digits, etc. A web application that graphically displays the results of Trump and Biden by state against Benford`s law The method is simple. Take the number of votes a candidate received in each riding and count their first number. Represent the total number of occurrences of each main digit (1-9) and the expected Benford values. Do you have a question about this project? Sign up for a free GitHub account to open a problem and contact managers and the community. This result has been shown to apply to a variety of data sets, including utility bills, mailing addresses, stock prices, house prices, population counts, mortality rates, river length, and physical and mathematical constants. It tends to be more accurate when values are spread over several orders of magnitude, especially when the process that generates the numbers is described by a power law (which is common in nature). If you have downloaded the app and need data. Go to the WI OPEN DATA —> here.