Dataset Card for 100 Richest People In World

  Dataset Summary

This dataset contains the list of Top 100 Richest People in the World Column Information:-

Name - Person Name NetWorth - His/Her Networth Age - Person Age Country - The country person belongs to Source - Information Source Industry - Expertise Domain

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  Supported Tasks and Leaderboards

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  Languages

[More Information Needed]… See the full description on the dataset page: https://huggingface.co/datasets/nateraw/100-richest-people-in-world.

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Analysis of ‘Ultimate UFC Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/mdabbert/ultimate-ufc-dataset on 21 November 2021.

--- Dataset description provided by original source is as follows ---

Project Title

Tiger Millionaire - UFC Fight Predictor

Full Documentation in the Wiki

Description

The goal of this project is to maintain the most complete UFC database that includes the following data sources:

• ufcstats.com - (bout and fighter statistics)
• bestfightodds.com - (odds)
• kaggle.com/martj42/ufc-rankings - (ufc rankings)

Getting Started

Start with the Wiki

Or go join a contest....

Contest

For every UFC event there will be a betting contest where users can train models to predict profitable bets (or just manually pick!). More details here: UFC Contest

Authors

Matt Dabbert On GitHub

Acknowledgments

Inspiration, code snippets, etc. * Rajeev Warrier's UFC Dataset

--- Original source retains full ownership of the source dataset ---

Introduction

In order to develop effective crowdsourcing aggregation methods for multiple choice question answering(MCQA) and evaluate them empirically, we developed and deployed a crowdsourced system for playing the “Who wants to be a millionaire?” quiz show. Note that, as question and answer texts are originally in Turkish you should use UTF8 format at all times to avoid encoding problems.

Citation

Harvard Aydin BI, Yilmaz YS, Demirbas M. A crowdsourced “Who wants to be a millionaire?” player. Concurrency Computat.: Pract. Exper. 2017;e4168. https://doi.org/10.1002/cpe.4168

Data

Over the period of 9 months, we collected over 3 GB of data using our CrowdMillionaire app. In our dataset, there are 1908 questions and 214,658 unique answers to those questions from CrowdMillionaire participants. In addition, we have more than 5 million offline answers for archived live questions. Our dataset includes detailed information on the game play. For example, our exhaustive timestamps show (1) how much time it took for a question to arrive to a participant, (2) when the question is actually presented to the participant on her device, and (3) when exactly the participant answered the question. We shared this dataset in order to advance the understanding of the MCQA dynamics, after we cleaned and anonymized the data.

Acknowlegement

Foto von Jason Leung auf Unsplash

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We rely on theories positing general resentment of the rich to argue that people who believe there are greater number of Justices who are millionaires will have more negative attitudes towards the Court than those who believe there are fewer millionaires on the Court. Analyzing the results to a nationally representative survey, we find that individuals who believe a larger number of the Justices are millionaires are more likely to believe the Court gives special rights to the wealth and overall are less likely to view the Court as legitimate. We supplement these results with a survey experiment which demonstrations that individuals believe the Court will become less fair if a millionaire nominee is confirmed to be a Justice and that individuals are less likely to support a millionaire nominee compared to nominees with a lower net worth. Our results have implications for perceptions of bias within the judiciary, the selection of judicial nominees, and how attitudes about the wealthy can influence attitudes towards institutions.

Abstract copyright UK Data Service and data collection copyright owner. The purpose of these data is to study the social origins and residual economic worth of elite individuals in British society, 1880-1970. Main Topics: Variables Sex, date of birth, elite category (e.g. Cabinet Ministers, peerage, landowners, millionaires, company chairmen), inherited title, highest created title, Government of first peerage creation, membership of Governments, primary and secondary occupations, place of secondary and higher education, religion, party afiliation, highest level of political participation, probate and land valuation, kinship with other wealth holders/other elites. Father: elite category, title, social class, occupation, probate and land valuation, date of death. Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research. No sampling (total universe) Compilation or synthesis of existing material

This statistic shows a ranking of the estimated number of High Net Worth Individuals (HNWI) in 2020 in Asia, differentiated by country. High Net Worth Individuals are here defined as persons with investible assets of at least 1 million US$ in current exchange rate terms.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

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