The dataset contains ranking-and-academic-year-, state-, and university/institute-wise compiled data on the total number of admitted, graduated and placed students of post and graduate students, along with additional details such as number of first year students intaken, number of admitted students through lateral entry, number of students selected for higher studies and median salary of students selected for placements, etc., as per the National Institutional Ranking Framework (NIRF) data

Data on the top universities for Computer Science in 2025.

This statistic provides a ranking of universities in the United States in 2015, by their number of Hispanic Master's degree graduates. In 2015, Florida International University conferred ***** Master's degrees to Hispanic students.

Data is from FiveThirtyEight's candy rankings. Data documentation is here: https://github.com/fivethirtyeight/data/blob/master/candy-power-ranking/README.md. The article describing the methodology and rankings is here: https://fivethirtyeight.com/videos/the-ultimate-halloween-candy-power-ranking/

Data on the top universities for Physical Sciences in 2025, including disciplines such as Chemistry, Geology, and Physics & Astronomy.

Data on the top universities for Engineering in 2025, including disciplines such as Chemical Engineering, Civil Engineering, and Mechanical and Aerospace Engineering.

Data on the top universities for Social Sciences in 2025, including disciplines such as Communication & Media Studies, Geography, and Sociology.

The measurement of change in biological systems through protein quantification is a central theme in modern biosciences and medicine. Label-free MS-based methods have greatly increased the ease and throughput in performing this task. Spectral counting is one such method that uses detected MS2 peptide fragmentation ions as a measure of the protein amount. The method is straightforward to use and has gained widespread interest. Additionally reports on new statistical methods for analyzing spectral count data appear at regular intervals, but a systematic evaluation of these is rarely seen. In this work, we studied how similar the results are from different spectral count data analysis methods, given the same biological input data. For this, we chose the algorithms Beta Binomial, PLGEM, QSpec, and PepC to analyze three biological data sets of varying complexity. For analyzing the capability of the methods to detect differences in protein abundance, we also performed controlled experiments by spiking a mixture of 48 human proteins in varying concentrations into a yeast protein digest to mimic biological fold changes. In general, the agreement of the analysis methods was not particularly good on the proteome-wide scale, as considerable differences were found between the different algorithms. However, we observed good agreements between the methods for the top abundance changed proteins, indicating that for a smaller fraction of the proteome changes are measurable, and the methods may be used as valuable tools in the discovery-validation pipeline when applying a cross-validation approach as described here. Performance ranking of the algorithms using samples of known composition showed PLGEM to be superior, followed by Beta Binomial, PepC, and QSpec. Similarly, the normalized versions of the same method, when available, generally outperformed the standard ones. Statistical detection of protein abundance differences was strongly influenced by the number of spectra acquired for the protein and, correspondingly, its molecular mass.

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Dataset: GR-SCBET-Y03Y07

Soccer bets and teams DB from coupons
Greece, Aug.2003 - Mar.2007

Release Notes

Copyright (c) 2016 by Harris V. Georgiou

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Release: Aug 3, 2016

- Version: 1.1a
- Format: .xls
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This file contains important information about the current version of the dataset package. Downloading and using this material hints that you accept the EULA/Terms-of-Use (please read carefully).

We welcome your comments and suggestions.

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WHAT'S IN THIS PACKAGE?

- Overview
- Available file formats
- Files and Datasets
- License Agreement

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OVERVIEW

Athletic betting and successful risk management is one of the most challenging tasks in Machine Learning and A.I. in general. With only limited information and very sparsely distributed data, an algorithm has to model the teams' competency and predict outcomes of games, even when two teams face each other for the first time.

This package contains two main datasets, generated from soccer betting coupons in Greece throughout a 3.5 year period and including every game that was included for any championship and any team. The first dataset corresponds to 43.758 matches with complete odds, final result and goals. The second is team-based statistics from these matches for a total of 1.126 teams from various championships (European and other).

These datasets can be used as benchmark training sets for odds-oriented or team-oriented predictive models and algorithms, relevant not only to athletic betting but also other contexts, lile in in financial risk management. In the case of team-oriented modeling, special ELO-like ranking algorithms can be developed and tested against the official team/country rankings, as in UEFA and FIFA, but tailored to specific teams or championships, in order to evaluate and fine-tune the models.

Note: Team names are in Greek, but they can be used as-is for proper referencing to unique IDs, i.e., practically they can be ignored.

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AVAILABLE FILE FORMATS

The datasets are available in the following formats (included):

*.xls : MS-Excel/LibreOffice worksheet data file (exportable)

Considering the three different types presented in this statistics, 'Pouches' leads the ranking with ********* people. Contrastingly, 'Foil trays' is ranked last, with *********** people.

Considering the three different types presented in this statistics, 'Tins' leads the French ranking with *** million people. Contrastingly, 'Pouches' is ranked last, with ****** thousand people. Their difference, compared to the Types, lies at ****** thousand people.

This study aims to analyze the adoption of Open Access (OA) publishing in social sciences within central universities in India, focusing on various aspects such as the growth of OA literature, the utilization of different OA routes, and collaboration patterns in OA publications.Ten central universities were selected based on their rankings in the National Institute Ranking Framework (NIRF) 2022. Data on OA publishing in social sciences were collected from the Social Science Citation Index of the Web of Science database using the advanced search query "(CU=India OR AD=India) AND PY=(2003-2022) NOT PY=(2023)". Data analysis was conducted using MS Excel (v16.0), BibExcel (version - 2017), Biblioshiny (version 4.1.2), and Google Open Refine (version 3.7).

In the academic year 2023/24, there were 331,602 international students from India studying in the United States. International students The majority of international students studying in the United States are originally from India and China, totaling 331,602 students and 277,398 students respectively in the 2023/24 school year. In 2022/23, there were 467,027 international graduate students , which accounted for over one third of the international students in the country. Typically, engineering and math & computer science programs were among the most common fields of study for these students. The United States is home to many world-renowned schools, most notably, the Ivy League Colleges which provide education that is sought after by both foreign and local students. International students and college Foreign students in the United States pay some of the highest fees in the United States, with an average of 24,914 U.S. dollars. American students attending a college in New England paid an average of 14,900 U.S. dollars for tuition alone and there were about 79,751 international students in Massachusetts . Among high-income families, U.S. students paid an average of 34,700 U.S. dollars for college, whereas the average for all U.S. families reached only 28,026 U.S. dollars. Typically, 40 percent of families paid for college tuition through parent income and savings, while 29 percent relied on grants and scholarships.

In 2023, the state of Mississippi had the highest infant mortality rate in the United States, with around 8.94 deaths per 1,000 live births. Infant mortality is the death of an infant before the age of one. The countries with the lowest infant mortality rates worldwide are Slovenia, Singapore, and Iceland. The countries with the highest infant mortality rates include Afghanistan, Somalia, and the Central African Republic. Infant mortality in the United States The infant mortality rate in the United States has decreased over the past few decades, reaching a low of 5.4 deaths per 1,000 live births in 2022. The most common causes of infant death in the United States are congenital malformations, low birth weight, and sudden infant death syndrome. In 2023, congenital malformations accounted for around 111 infant deaths per 100,000 live births.

As of November 2023, Novak Djokovic topped the rankings of male professional tennis players with the most ATP Masters 1000 titles. In a career that began in 2003, the Serbian won a staggering ** ATP Masters 1000 titles, the latest of which came during the 2023 Rolex Paris Masters against Bulgarian Grigor Dimitrov. In second place was Spaniard Rafael Nadal with ** titles.

In 2020, Memphis, TN-MS-AR reported 1,358.8 violent crimes per 100,000 inhabitants, the most out of any metro area in the United States. Monroe, LA followed closely behind, with a violent crime rate of 1,308.5 crimes per 100,000 inhabitants.

In 2021-2022, Mississippi topped the ranking of states with the highest share of children/adolescents between 6 and 17 years of age who were obese. This statistic illustrates the obesity rates among children/adolescents between 6 and 17 years of age in the United States in 2021-2022, by state.

West Virginia and Kansas had the lowest cost of living across all U.S. states, with composite costs being half of those found in Hawaii. This was according to a composite index that compares prices for various goods and services on a state-by-state basis. In West Virginia, the cost of living index amounted to **** — well below the national benchmark of 100. Virginia— which had an index value of ***** — was only slightly above that benchmark. Expensive places to live included Hawaii, Massachusetts, and California. Housing costs in the U.S. Housing is usually the highest expense in a household’s budget. In 2023, the average house sold for approximately ******* U.S. dollars, but house prices in the Northeast and West regions were significantly higher. Conversely, the South had some of the least expensive housing. In West Virginia, Mississippi, and Louisiana, the median price of the typical single-family home was less than ******* U.S. dollars. That makes living expenses in these states significantly lower than in states such as Hawaii and California, where housing is much pricier. What other expenses affect the cost of living? Utility costs such as electricity, natural gas, water, and internet also influence the cost of living. In Alaska, Hawaii, and Connecticut, the average monthly utility cost exceeded *** U.S. dollars. That was because of the significantly higher prices for electricity and natural gas in these states.